Refrigeration abnormality monitoring method and system for refrigeration station

Abstract

The present application relates to the field of refrigeration plant monitoring technology, and specifically to a method and system for supervising refrigeration anomalies in refrigeration plants. The method includes obtaining the refrigeration equipment operation data of the calibrated refrigeration equipment in the current refrigeration plant, and judging whether the current refrigeration plant is in an abnormal refrigeration state; if the judgment is yes, obtaining the refrigeration plant association sequence, determining the refrigeration associated plant and the refrigeration associated calibration equipment; obtaining the associated plant real-time monitoring data, and judging whether the overall operation monitoring data of the current refrigeration plant matches the associated plant real-time monitoring data, and if the judgment is yes, generating an associated equipment operation difference value; judging whether the associated equipment operation difference value is less than or equal to a preset associated equipment difference threshold, and if the judgment is yes, generating a refrigeration fault prediction indication. The present application achieves further refined operation analysis by comparing the operation data of the associated equipment, thereby achieving accurate supervision of whether a refrigeration plant has a fault.

Description

Technical Field

[0001] The present application relates to the technical field of refrigeration station monitoring, and in particular to a method and system for monitoring refrigeration abnormalities in a refrigeration station. Background Art

[0002] Refrigeration plants are mainly used to provide cooling support for industrial production, commercial buildings, data centers and other places that require stable and reliable cooling supply. In order to ensure stable cooling, it is necessary to ensure that the refrigeration function of the refrigeration plant is normal. Therefore, the operation monitoring of the refrigeration plant is very important.

[0003] In the prior art, for example, a Chinese invention patent with publication number CN118623517A disclosed on September 10, 2024 a refrigeration unit control method and system based on data monitoring, which relates to the technical field of refrigeration units. The refrigeration unit control method based on data monitoring includes the following steps: obtaining the operating characteristic data of the refrigeration unit; identifying abnormal data of the current operating status of the refrigeration unit; evaluating the key factors affecting the operating status of the refrigeration unit; determining whether it matches the known operating failure mode of the refrigeration unit, and adjusting the operating parameters of the refrigeration unit.

[0004] Although the technical solution in the above patent document can detect abnormal situations, perform preventive maintenance, and avoid production interruptions and repair costs caused by sudden failures, it directly monitors the data of the entire refrigeration unit, which easily leads to the problem of waste of monitoring resources. On the other hand, the standard data used to evaluate whether there is an abnormality is the conventional historical data in the past, and does not take into account the different operating parameters caused by differences in production batches of refrigeration equipment, which in turn leads to inaccurate standard data, thereby affecting the judgment accuracy of refrigeration abnormalities and resulting in low accuracy of abnormal judgment. Summary of the invention

[0005] Based on this, it is necessary to provide a refrigeration abnormality monitoring method and system for refrigeration stations that can save monitoring resources and conduct refined analysis, as well as provide a reference for fault judgment by determining related stations and equipment, and then achieve further refined operation analysis by comparing the operating data of related equipment, thereby achieving high-precision supervision and analysis of whether there is a fault in the refrigeration station.

[0006] The technical solution of the present invention is as follows:

[0007] A method for supervising abnormal refrigeration in a refrigeration station, the method comprising:

[0008] Acquire the refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration station, and determine whether the current refrigeration station is in an abnormal refrigeration state according to the refrigeration equipment operation data;

[0009] If the judgment is yes, then obtaining the refrigeration plant association sequence of the current refrigeration plant, and determining the refrigeration associated plant and the refrigeration associated calibration equipment according to the refrigeration plant association sequence;

[0010] Acquire the associated station real-time monitoring data of the refrigeration associated station, and determine whether the overall operation monitoring data of the current refrigeration station matches the associated station real-time monitoring data, and if so, generate an associated equipment operation difference value according to the refrigeration associated calibration device and the current refrigeration station;

[0011] It is determined whether the associated equipment operation difference value is less than or equal to a preset associated equipment difference threshold value. If it is determined to be yes, a refrigeration fault prediction indication is generated, and the current refrigeration plant is inspected and repaired according to the refrigeration fault prediction indication.

[0012] Optionally, the calibrated refrigeration device is a first compressor;

[0013] Acquiring refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration station, and judging whether the current refrigeration station is in an abnormal refrigeration state according to the refrigeration equipment operation data, including:

[0014] Acquire the refrigeration equipment operation data of the first compressor pre-calibrated in the current refrigeration station, collect data according to the preset power collection time point and obtain the refrigeration collection point data, wherein one power collection time point corresponds to one refrigeration collection point data;

[0015] Generate a refrigeration operation load rate of the first compressor according to the refrigeration collection point data, wherein one refrigeration collection point data corresponds to one refrigeration operation load rate;

[0016] Screening out the refrigeration operation load rate within the refrigeration load rate calibration range and recording it as the overload load rate, wherein the refrigeration load rate calibration range is preset;

[0017] Calculate the overload intervals of adjacent overload load rates, obtain the overload intervals that are less than the overload time threshold, and record them as high-frequency time intervals, wherein the number of the high-frequency time intervals is n, and one high-frequency time interval corresponds to two overload load rates;

[0018] Obtaining the average of two overload load rates corresponding to the high-frequency time interval and recording it as a first average, wherein one high-frequency time interval corresponds to one first average;

[0019] generating an overload cooling fluctuation index according to the overload load rate, the high frequency time interval, the overload time threshold, and the first mean value;

[0020] Determining whether the overload cooling fluctuation index is greater than or equal to the overload cooling fluctuation threshold;

[0021] If the judgment is yes, then it is judged that the current refrigeration station is in an abnormal refrigeration state;

[0022] If the judgment is no, it is determined that the current refrigeration station is not in an abnormal refrigeration state.

[0023] Optionally, an overload cooling fluctuation index is generated based on the following formula:

[0024] ;

[0025] Among them, Do is the index for generating overload cooling fluctuation, n is the number of high-frequency time intervals, ST is the overload time threshold, Tvi is the i-th high-frequency time interval, Ui is the first mean value corresponding to the i-th high-frequency time interval, and SU is the mean value of each overload load rate.

[0026] Optionally, the refrigeration plant association sequence includes multiple refrigeration plants of the same type, and each of the refrigeration plants of the same type is produced in the same batch as the current refrigeration plant;

[0027] Determining a refrigeration-related station and a refrigeration-related calibration device according to the refrigeration station association sequence includes:

[0028] Obtaining the refrigeration usage time of each refrigeration room of the same type in the refrigeration room association sequence, and recording the refrigeration room of the same type corresponding to the refrigeration usage time greater than or equal to the refrigeration usage calibration time as the first screening room;

[0029] Extracting the first screening station equipment operating environment data of the first screening station;

[0030] Extracting ambient temperature data, ambient humidity data and operating building insulation data from the first screening station equipment operating environment data, and generating the ambient temperature range, ambient humidity range and building insulation range of the same type of station;

[0031] Acquire current station building environmental data of the current refrigeration station building, and select a second screening station building from the first screening station building according to the current station building environmental data, the environmental temperature range of the same type of station building, the environmental humidity range of the same type of station building, and the thermal insulation range of the same type of station building;

[0032] Extracting operation data of a same-type station building of the second screening station building, and extracting a refrigeration demand range of the second screening station building from the operation data of the same-type station building;

[0033] Acquire the completed refrigeration demand of the current refrigeration plant, and generate a completed demand range according to the completed refrigeration demand;

[0034] The second screening station corresponding to the refrigeration demand range including the completed demand range is set as a refrigeration-related station, and a refrigeration-related calibration device is set according to the refrigeration-related station.

[0035] Optionally, obtaining the associated station real-time monitoring data of the refrigeration associated station, and judging whether the overall operation monitoring data of the current refrigeration station matches the associated station real-time monitoring data, comprises:

[0036] Acquire the real-time monitoring data of the associated station of the refrigeration associated station, and acquire the overall operation monitoring data of the current refrigeration station;

[0037] Extracting a first operating parameter range from the real-time monitoring data of the associated station building according to the preset station building power, and extracting a second operating parameter range from the overall operation monitoring data;

[0038] determining whether the first operating parameter range includes the second operating parameter range;

[0039] If the judgment is yes, then judging whether the overall operation monitoring data of the current refrigeration plant matches the real-time monitoring data of the associated plant;

[0040] If the judgment is no, it is determined that the overall operation monitoring data of the current refrigeration plant does not match the real-time monitoring data of the associated plant.

[0041] Optionally, the calibrated refrigeration equipment is the first compressor in the current refrigeration plant, and the refrigeration-related calibration equipment is the second compressor in the refrigeration-related plant;

[0042] Generate an associated equipment operation difference value according to the refrigeration associated calibration equipment and the current refrigeration plant, including:

[0043] Applying a supervisory test excitation to the first compressor and the second compressor, and acquiring first vibration detection data collected by the first compressor at a preset reference position and second vibration detection data collected by the second compressor at a preset reference position, wherein the preset reference position is a cylinder body beside an exhaust valve of the first compressor and the second compressor;

[0044] generating a first vibration information set according to the first vibration detection data, and generating a second vibration information set according to the second vibration detection data;

[0045] Acquire first exhaust temperature data collected by the first compressor at a preset reference position and second exhaust temperature data collected by the second compressor at a preset reference position;

[0046] calculating a first deviation value between the first exhaust temperature data and a preset average temperature, and calculating a second deviation value between the second exhaust temperature data and the preset average temperature, wherein the preset average temperature corresponds to the regulatory test stimulus;

[0047] An associated equipment operation difference value is generated according to the first vibration information set, the second vibration information set, the first deviation value, and the second deviation value.

[0048] Optionally, the associated device operation difference value is generated based on the following formula:

[0049] ;

[0050] Among them, Rdv is the operating difference value of the associated equipment, is the vibration information weight, k is the number of cylinder vibration values ​​in the first vibration information set, Faj is the jth cylinder vibration value in the first vibration information set, is the mean value of the cylinder vibration value in the first vibration information set, Fbj is the jth cylinder vibration value in the second vibration information set, is the mean value of the cylinder vibration value in the second vibration information set, is the temperature information weight, is the first deviation value, is the second deviation value.

[0051] The present application also provides a refrigeration abnormality monitoring system for a refrigeration station, the system comprising:

[0052] A refrigeration monitoring start module is used to obtain the refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration station, and determine whether the current refrigeration station is in an abnormal refrigeration state according to the refrigeration equipment operation data;

[0053] an associated device determination module, for obtaining a refrigeration plant association sequence of the current refrigeration plant if the determination is yes, and determining a refrigeration associated plant and a refrigeration associated calibration device according to the refrigeration plant association sequence;

[0054] An operation parameter comparison module is used to obtain the real-time monitoring data of the associated station of the refrigeration associated station, and determine whether the overall operation monitoring data of the current refrigeration station matches the real-time monitoring data of the associated station. If the determination is yes, an associated equipment operation difference value is generated according to the refrigeration associated calibration equipment and the current refrigeration station;

[0055] The supervision result generation module is used to determine whether the operation difference value of the associated equipment is less than or equal to a preset associated equipment difference threshold. If it is determined to be yes, a refrigeration fault prediction indication is generated, and the current refrigeration station is inspected and repaired according to the refrigeration fault prediction indication.

[0056] Optionally, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps described in the above-mentioned refrigeration abnormality monitoring method for a refrigeration station when executing the computer program.

[0057] Optionally, a computer-readable storage medium is also provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps described in the above-mentioned refrigeration abnormality monitoring method for a refrigeration station are implemented.

[0058] The technical effects achieved by the present invention are as follows:

[0059] The above-mentioned refrigeration abnormality supervision method and system of the refrigeration station obtains the refrigeration equipment operation data of the calibrated refrigeration equipment in the current refrigeration station, and judges whether the current refrigeration station is in a refrigeration abnormality state according to the refrigeration equipment operation data; if it is judged to be yes, then the refrigeration station association sequence of the current refrigeration station is obtained, and the refrigeration associated station and the refrigeration associated calibration equipment are determined according to the refrigeration station association sequence; the associated station real-time monitoring data of the refrigeration associated station is obtained, and it is judged whether the overall operation monitoring data of the current refrigeration station matches the associated station real-time monitoring data, if it is judged to be yes, then the associated equipment operation difference value is generated according to the refrigeration associated calibration equipment and the current refrigeration station; it is judged whether the associated equipment operation difference value is less than or equal to the preset associated equipment difference threshold value, if it is judged to be yes, then a refrigeration fault prediction indication is generated, and the current refrigeration station is inspected according to the refrigeration fault prediction indication, and the refrigeration fault prediction indication is used to inspect the current refrigeration station in advance. Equipment that is prone to damage and prone to refrigeration abnormalities is selected from the stored refrigeration equipment loss database and calibrated as the calibrated refrigeration equipment. By pre-setting the calibrated refrigeration equipment, accurate monitoring of equipment that often fails and is prone to failure is achieved. Compared with the waste of monitoring resources caused by directly monitoring all refrigeration equipment in the prior art, the present application saves monitoring resources, and by first performing data analysis on a small number of calibrated refrigeration equipment, it can achieve point-to-point refined analysis and abnormality diagnosis, specifically obtaining the refrigeration equipment operation data of the calibrated refrigeration equipment in the current refrigeration station, and judging whether the current refrigeration station is in an abnormal refrigeration state based on the refrigeration equipment operation data. The abnormal refrigeration state is that the operation of the calibrated refrigeration equipment in the current refrigeration station is in a state of large fluctuation. If the judgment is no, it means that the refrigeration operation of the current refrigeration station is normal at this time, and the operation monitoring can continue at this time.If the judgment is yes, that is, it is judged that the current refrigeration plant is in a refrigeration abnormality state, it means that a refrigeration abnormality may occur at this time or it is in the early stage of a failure. In order to further judge whether a failure may occur or cause more serious refrigeration abnormality or loss, the refrigeration plant association sequence of the current refrigeration plant is obtained, and the refrigeration associated plant and refrigeration associated calibration equipment are determined according to the refrigeration plant association sequence. The refrigeration associated plant is a plant with a similar equipment condition to the current refrigeration plant, and the refrigeration associated calibration equipment is a refrigeration equipment corresponding to the calibrated refrigeration equipment, which is at least produced in the same batch as the current refrigeration plant and For the refrigeration plant that was put into use earlier than the current refrigeration plant, the refrigeration plant association sequence is set, and the refrigeration associated plant and refrigeration associated calibration equipment are determined based on the refrigeration plant association sequence, so that the associated refrigeration equipment and plant are used to provide monitoring references, thereby improving the reliability of supervision. Then, the associated plant real-time monitoring data of the refrigeration associated plant is obtained, and it is determined whether the refrigeration equipment operation data matches the associated plant real-time monitoring data. If the judgment is no, it is determined that the refrigeration equipment operation data does not match the associated plant real-time monitoring data. Therefore, it can be determined that there is no trend of failure, and the maintenance can be carried out directly at this time. If the judgment is yes, then in order to judge whether the operation data of the refrigeration equipment matches the real-time monitoring data of the associated station, it is not directly judged that there is no abnormality at this time, but further data analysis is performed, specifically, the associated equipment operation difference value is generated according to the refrigeration associated calibration equipment and the current refrigeration station, and finally it is judged whether the associated equipment operation difference value is less than or equal to the preset associated equipment difference threshold value. If the judgment is no, it means that the difference between the calibrated refrigeration equipment in the current refrigeration station and the refrigeration associated calibration equipment corresponding to the refrigeration associated station as the standard reference is small, so it can be judged that there is no fault trend at this time. If the judgment is yes, a refrigeration fault prediction indication is generated, and the current refrigeration station is analyzed according to the refrigeration fault prediction indication. Therefore, the present application first saves monitoring resources and refined analysis by setting the calibrated refrigeration equipment and performing refrigeration data analysis of the equipment, and then realizes the reference of fault judgment by determining the associated station and equipment, and then realizes further refined operation analysis by comparing the operation data of the associated equipment, thereby realizing accurate supervision of whether the refrigeration station has a fault. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A schematic diagram of a flow chart of a method for supervising abnormal refrigeration in a refrigeration station in an embodiment;

[0061] Figure 2 The structure diagram of the abnormal refrigeration monitoring system of a refrigeration plant in one embodiment is shown. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] In one embodiment, Figure 1 As shown, a method for supervising abnormal refrigeration in a refrigeration station is provided, the method comprising:

[0064] Step S100: obtaining refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration plant, and judging whether the current refrigeration plant is in an abnormal refrigeration state according to the refrigeration equipment operation data;

[0065] Step S200: If the judgment is yes, then obtain the refrigeration plant association sequence of the current refrigeration plant, and determine the refrigeration-associated plant and the refrigeration-associated calibration equipment according to the refrigeration plant association sequence;

[0066] Step S300: acquiring the associated station real-time monitoring data of the refrigeration associated station, and determining whether the overall operation monitoring data of the current refrigeration station matches the associated station real-time monitoring data; if so, generating an associated equipment operation difference value according to the refrigeration associated calibration device and the current refrigeration station;

[0067] Step S400: determining whether the associated equipment operation difference value is less than or equal to a preset associated equipment difference threshold value; if so, generating a refrigeration fault prediction indication, and inspecting the current refrigeration plant room according to the refrigeration fault prediction indication.

[0068] In this embodiment, in order to perform abnormal monitoring and fault prediction of the refrigeration situation of the refrigeration station, a calibrated refrigeration device is first pre-set, and the calibrated refrigeration device is pre-selected from the refrigeration devices in the current refrigeration station. The device that is prone to damage and prone to refrigeration abnormality is selected from the pre-stored refrigeration device loss database and calibrated as the calibrated refrigeration device. By pre-setting the calibrated refrigeration device, accurate monitoring of the equipment that often fails and is prone to failure is achieved. Compared with the waste of monitoring resources caused by directly monitoring all refrigeration equipment in the prior art, the present application saves monitoring resources, and by first performing data analysis on a small number of calibrated refrigeration devices, point-to-point refined analysis and abnormal diagnosis can be achieved. Specifically, the refrigeration device operation data of the calibrated refrigeration device in the current refrigeration station is obtained, and according to the refrigeration device operation data, it is determined whether the current refrigeration station is in a refrigeration abnormal state. The refrigeration abnormal state is that the operation of the calibrated refrigeration device in the current refrigeration station is in a state of large fluctuation. If it is judged as no, it means that the refrigeration operation of the current refrigeration station is normal at this time, and the operation monitoring can be continued at this time. If the judgment is yes, that is, it is judged that the current refrigeration plant is in a refrigeration abnormality state, it means that a refrigeration abnormality may occur at this time or it is in the early stage of a failure. In order to further judge whether a failure may occur or cause more serious refrigeration abnormality or loss, the refrigeration plant association sequence of the current refrigeration plant is obtained, and the refrigeration associated plant and refrigeration associated calibration equipment are determined according to the refrigeration plant association sequence. The refrigeration associated plant is a plant with a similar equipment condition to the current refrigeration plant, and the refrigeration associated calibration equipment is a refrigeration equipment corresponding to the calibrated refrigeration equipment, which is at least produced in the same batch as the current refrigeration plant and For the refrigeration plant that was put into use earlier than the current refrigeration plant, the refrigeration plant association sequence is set, and the refrigeration associated plant and refrigeration associated calibration equipment are determined based on the refrigeration plant association sequence, so that the associated refrigeration equipment and plant are used to provide monitoring references, thereby improving the reliability of supervision. Then, the associated plant real-time monitoring data of the refrigeration associated plant is obtained, and it is determined whether the refrigeration equipment operation data matches the associated plant real-time monitoring data. If the judgment is no, it is determined that the refrigeration equipment operation data does not match the associated plant real-time monitoring data. Therefore, it can be determined that there is no trend of failure, and the maintenance can be carried out directly at this time.If the judgment is yes, then in order to judge whether the operation data of the refrigeration equipment matches the real-time monitoring data of the associated station, it is not directly judged that there is no abnormality at this time, but further data analysis is performed, specifically, the associated equipment operation difference value is generated according to the refrigeration associated calibration equipment and the current refrigeration station, and finally it is judged whether the associated equipment operation difference value is less than or equal to the preset associated equipment difference threshold value. If the judgment is no, it means that the difference between the calibrated refrigeration equipment in the current refrigeration station and the refrigeration associated calibration equipment corresponding to the refrigeration associated station as the standard reference is small, so it can be judged that there is no fault trend at this time. If the judgment is yes, a refrigeration fault prediction indication is generated, and the current refrigeration station is analyzed according to the refrigeration fault prediction indication. Therefore, the present application first saves monitoring resources and refined analysis by setting the calibrated refrigeration equipment and performing refrigeration data analysis of the equipment, and then realizes the reference of fault judgment by determining the associated station and equipment, and then realizes further refined operation analysis by comparing the operation data of the associated equipment, thereby realizing accurate supervision of whether the refrigeration station has a fault.

[0069] In one embodiment, the calibrated refrigeration device is a first compressor;

[0070] In step S100, the refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration plant is obtained, and it is determined whether the current refrigeration plant is in an abnormal refrigeration state according to the refrigeration equipment operation data, including:

[0071] Step S110: obtaining refrigeration equipment operation data of a pre-calibrated first compressor in the current refrigeration station, performing data collection according to a preset power collection time point and obtaining refrigeration collection point data, wherein one power collection time point corresponds to one refrigeration collection point data;

[0072] Step S120: generating a refrigeration operation load rate of the first compressor according to the refrigeration collection point data, wherein one refrigeration collection point data corresponds to one refrigeration operation load rate;

[0073] Specifically, the first compressor is pre-calibrated as a calibrated refrigeration device, that is, the compressor is considered to be the core refrigeration facility in this application, so the compressor is used as an example for explanation. In steps S110-S120, in order to accurately judge whether the refrigeration is abnormal, the load rate is generated first, firstly, the power collection time point is pre-set so that uniform data collection can be performed, specifically, the refrigeration equipment operation data of the first compressor in the current refrigeration station is first obtained, and data is collected according to the preset power collection time point and the refrigeration collection point data is obtained, and then the refrigeration operation load rate of the first compressor is generated according to the refrigeration collection point data, wherein one refrigeration collection point data corresponds to one refrigeration operation load rate.

[0074] Furthermore, a cooling operation load factor is calculated based on the following formula:

[0075] ;

[0076] Wherein, We is the refrigeration operation load rate, V is the voltage of the power supply of the first compressor, I is the working current of the motor of the first compressor, pf is the power factor, and Wr is the rated power.

[0077] Among them, the voltage of the power supply of the first compressor and the working current of the motor of the first compressor are extracted from the refrigeration collection point data. The power factor is set based on the motor of the first compressor, and its specific value is determined by the motor, such as a general value of 0.78-0.82. The rated power is pre-set and stored. The actual refrigeration power is obtained by multiplying the voltage of the power supply of the first compressor, the working current of the motor of the first compressor and the power factor, and then divided by the rated power to obtain the refrigeration operation load rate.

[0078] Step S130: screening out the refrigeration operation load rate within the refrigeration load rate calibration range and recording it as the overload load rate, wherein the refrigeration load rate calibration range is preset;

[0079] In this step, the calibration range of the refrigeration load rate is a range that is about to reach the fault load rate but has not reached the fault load rate. For example, when the fault load rate is 100%, the calibration range of the refrigeration load rate can be any one of 95%-99%, 96%-99%, and 97%-99%. By pre-calibrating the calibration range of the refrigeration load rate, reference data for refrigeration abnormality can be set, and further analysis can be performed to determine whether the refrigeration fluctuates too much and is in an abnormal state by analyzing whether the first compressor is intermittently in or is about to be in a high-load operation state for a long time.

[0080] Step S140: calculating the overload intervals of adjacent overload load rates, obtaining the overload intervals that are less than the overload time threshold, and recording them as high-frequency time intervals, wherein the number of the high-frequency time intervals is n, and one high-frequency time interval corresponds to two overload load rates;

[0081] Step S150: obtaining the average of two overload load rates corresponding to the high-frequency time interval and recording it as a first average, wherein one high-frequency time interval corresponds to one first average;

[0082] In step S140-150, the overload time threshold is pre-set, and the overload time threshold is generally set to 5 minutes. The overload load rate of one overload load rate and the other overload load rate usually do not appear continuously. If the interval between the overload load rate of one overload load rate and the other overload load rate is large, it can usually be judged that it is a normal working state of inevitable intermittent overload work, but if it appears multiple times in a short period of time, it can be judged that it is a state of abnormal fluctuation, that is, if there are at least 2 overload load rates within the time length corresponding to the overload time threshold, further analysis is required. Therefore, the overload interval time of adjacent overload load rates is calculated first, and the overload interval time less than the overload time threshold is obtained, and recorded as a high-frequency time interval. Then, the mean of the two overload load rates corresponding to the high-frequency time interval is obtained and recorded as a first mean, wherein one high-frequency time interval corresponds to a first mean. The first mean is a value generated by adding two overload load rates and dividing by 2.

[0083] Step S160: generating an overload cooling fluctuation index according to the overload load rate, the high frequency time interval, the overload time threshold, and the first mean value;

[0084] Step S170: determining whether the overload cooling fluctuation index is greater than or equal to the overload cooling fluctuation threshold;

[0085] Step S180: If the answer is yes, then determine that the current refrigeration station is in an abnormal refrigeration state;

[0086] Step S190: If the judgment is no, it is determined that the current refrigeration station is not in an abnormal refrigeration state.

[0087] In this embodiment, an overload refrigeration fluctuation index is generated by combining the overload load rate, high-frequency time interval, overload time threshold, and the first mean value, and the overload refrigeration fluctuation threshold is pre-set, so that when it is judged that the overload refrigeration fluctuation index is greater than or equal to the overload refrigeration fluctuation threshold, it means that the overload working state occupies a large proportion at this time, so a fault may occur, and it is necessary to first determine that it belongs to an abnormal refrigeration state, so as to further perform subsequent fault analysis and supervision, that is, at this time, it is judged that the current refrigeration station is in an abnormal refrigeration state. On the contrary, if it is judged that the overload refrigeration fluctuation index is less than the overload refrigeration fluctuation threshold, it means that the refrigeration state is normal, and then it is judged that the current refrigeration station is not in an abnormal refrigeration state, and then go to step S021. Step S021 is explained later.

[0088] In one embodiment, the overload cooling fluctuation index is generated based on the following formula:

[0089] ;

[0090] Among them, Do is the index for generating overload cooling fluctuation, n is the number of high-frequency time intervals, ST is the overload time threshold, Tvi is the i-th high-frequency time interval, Ui is the first mean value corresponding to the i-th high-frequency time interval, and SU is the mean value of each overload load rate.

[0091] In one embodiment, the refrigeration plant association sequence includes multiple refrigeration plants of the same type, and each of the refrigeration plants of the same type is produced in the same batch as the current refrigeration plant;

[0092] In step S200, determining the refrigeration-related plant and the refrigeration-related calibration equipment according to the refrigeration plant association sequence includes:

[0093] Step S210: obtaining the refrigeration usage time of each refrigeration room of the same type in the refrigeration room association sequence, and recording the refrigeration room of the same type corresponding to the refrigeration usage time greater than or equal to the refrigeration usage calibration time as the first screening room;

[0094] In this step, by obtaining the refrigeration use time of the same type of refrigeration plant, the refrigeration units of the same batch that have been put into use can be screened out. Compared with the current refrigeration unit, this reduces the error of the operating data caused by production and improves the referenceability. The refrigeration use calibration time is generally set to half a year. By screening out the same type of refrigeration plants that have been put into use and are operating normally and setting them as the first screening plant, reliable data support is provided for the subsequent accurate supervision of refrigeration abnormalities.

[0095] Step S220: extracting the first screening station equipment operating environment data of the first screening station;

[0096] Step S230: extracting ambient temperature data, ambient humidity data and operating building insulation data from the first screening station room equipment operating environment data, and generating the ambient temperature range, ambient humidity range and building insulation range of the same type of station room;

[0097] Step S240: obtaining the current station room environment data of the current refrigeration station room, and selecting the second screening station room from the first screening station rooms according to the current station room environment data, the environmental temperature range of the same type of station rooms, the environmental humidity range of the same type of station rooms, and the thermal insulation range of the same type of station rooms;

[0098] In this step, the current station room temperature data, the current station room humidity data and the current station room building insulation data are extracted from the current station room environment data. Then, the current station room environment temperature range, the current station room environment humidity range and the current station room building insulation range are generated respectively according to the current station room temperature data, the current station room humidity data and the current station room building insulation data.

[0099] Among them, the maximum value and minimum value of the current station room ambient temperature range are the maximum value and minimum value in the current station room temperature data. The maximum value and minimum value of the current station room ambient humidity range are the maximum value and minimum value in the current station room humidity data. The current station room building insulation range is set according to the current station room building insulation data. Specifically, the current station room building insulation data includes the building main body where the current refrigeration station room is installed, and is mainly determined by the thickness of the building material of the building main body.

[0100] Furthermore, a method for setting the thermal insulation range of the current station building is provided:

[0101] The current station building insulation data includes the thickness d of the building material. The thermal conductivity of the building material is represented by R, which can generate the insulation coefficient Ur.

[0102] The calculation formula of thermal insulation coefficient Ur is as follows:

[0103] .

[0104] Furthermore, a basic insulation fluctuation range is set, and the minimum and maximum values ​​of the range are represented by Umin and Umax respectively. The minimum and maximum values ​​of the current station building insulation range are Umin*Ur and Umax*Ur respectively.

[0105] Similarly, the method for setting the ambient temperature range of the same type of station building, the ambient humidity range of the same type of station building and the thermal insulation range of the same type of station building is the same as the method for setting the current station building ambient temperature range, the current station building ambient humidity range and the current station building thermal insulation range. Those skilled in the art should know and master how to set them, so this application will not go into details.

[0106] Next, the Hausdorff distance between the ambient temperature range of the same type of station building and the ambient temperature range of the current station building is calculated, recorded as the first Hausdorff distance; the Hausdorff distance between the ambient humidity range of the same type of station building and the ambient humidity range of the current station building is calculated, recorded as the second Hausdorff distance; the Hausdorff distance between the thermal insulation range of the same type of station building and the thermal insulation range of the current station building is calculated, recorded as the third Hausdorff distance. Then, the first standard distance, the second standard distance, and the third standard distance are also preset.

[0107] The first screening station corresponding to the first Hausdorff distance being smaller than the first standard distance, the second Hausdorff distance being smaller than the second standard distance, and the third Hausdorff distance being smaller than the third standard distance is set as the second screening station.

[0108] Of course, the comparison can also be performed by calculating the Jaccard similarity, which is not specifically limited in this application.

[0109] Therefore, by calculating the environmental factors, mainly through the analysis of temperature data, humidity data and building insulation data, it is ensured that the second screening station selected is similar to the current refrigeration unit in installation environment and operating environment. This can ensure accurate reference and improve the accuracy of subsequent refrigeration supervision and judgment.

[0110] Step S250: extracting the operation data of the same type of station building as the second screening station building, and extracting the refrigeration demand range of the second screening station building from the operation data of the same type of station building;

[0111] Step S260: Acquire the completed refrigeration demand of the current refrigeration plant, and generate a completed demand range according to the completed refrigeration demand;

[0112] Step S270: setting the second screening station corresponding to the refrigeration demand range including the completed demand range as a refrigeration-related station, and setting a refrigeration-related calibration device according to the refrigeration-related station.

[0113] In step S250-step S270, firstly, the operation data of the same type of station of the second screening station is extracted, and the refrigeration demand range of the second screening station is extracted from the operation data of the same type of station, the refrigeration demand range is the refrigeration demand that has been executed by the second screening station, and then the completed refrigeration demand of the current refrigeration station is obtained, the completed refrigeration demand is the demand that has been completed by the current refrigeration station, and then the completed demand range is generated according to the completed refrigeration demand, and then the second screening station corresponding to the refrigeration demand range including the completed demand range is set as the refrigeration associated station, so that the refrigeration demand of the refrigeration associated station is greater than that of the current refrigeration station. On the premise that the associated refrigeration station and the current refrigeration station are produced in the same batch, the fact that the tasks that have been executed by the current refrigeration station means that the working parameters and status can be used as data reference for the current refrigeration station, thereby reducing the probability of mismatch of operating parameters caused by differences in usage.

[0114] Furthermore, the refrigeration-related calibration equipment is pre-set to be the same as the calibrated refrigeration equipment in the current refrigeration plant, that is, both are compressors, and the refrigeration-related calibration equipment is represented by a second compressor.

[0115] Furthermore, if only step S270 is performed, the number of the refrigeration-related stations may be multiple. In this case, each of the refrigeration-related stations needs to perform steps S300 to S400, and as long as the associated equipment operation difference values ​​corresponding to any refrigeration-related station are less than or equal to the preset associated equipment difference threshold, a refrigeration fault prediction indication is generated.

[0116] Of course, there is also a situation where there is only one refrigeration-associated station room. Specifically, when setting the refrigeration-associated station room, the second screening station room corresponding to the refrigeration demand range that includes the completed demand range and has the smallest difference with the completed demand range is set as the refrigeration-associated station room. At this time, there is only one refrigeration-associated station room.

[0117] In one embodiment, obtaining the real-time monitoring data of the associated station of the refrigeration associated station, and determining whether the overall operation monitoring data of the current refrigeration station matches the real-time monitoring data of the associated station, includes:

[0118] Step S311: obtaining the real-time monitoring data of the associated station of the refrigeration associated station, and obtaining the overall operation monitoring data of the current refrigeration station;

[0119] Step S312: extracting a first operating parameter range from the real-time monitoring data of the associated station building according to the preset station building power, and extracting a second operating parameter range from the overall operation monitoring data;

[0120] Step S313: determining whether the first operating parameter range includes the second operating parameter range;

[0121] Step S314: If the judgment is yes, then determine whether the overall operation monitoring data of the current refrigeration plant matches the real-time monitoring data of the associated plant;

[0122] Step S315: If the judgment is no, it is determined that the overall operation monitoring data of the current refrigeration plant does not match the real-time monitoring data of the associated plant.

[0123] In this embodiment, the real-time monitoring data of the associated station and the overall operation monitoring data are data collected and obtained from the current moment. In this way, the overall operation status between the refrigeration associated station and the current refrigeration station can be compared according to the current actual situation. The real-time monitoring data of the associated station and the overall operation monitoring data are the operation data of each part of the refrigeration associated station and the current refrigeration station, respectively. Specifically, a preset station power is pre-set, and the first operation parameter range is extracted from the real-time monitoring data of the associated station according to the preset station power, and the second operation parameter range is extracted from the overall operation monitoring data. That is, the operation parameter range corresponding to the same power is extracted from the overall operation data. If it is judged that the first operation parameter range does not include the second operation parameter range, it means that the operation parameters of the current refrigeration station at this time are parameters that have never appeared in the refrigeration associated station as a standard reference object, so it can be judged that the operation of the current refrigeration station is abnormal, and then maintenance is required, and fault maintenance can be directly performed at this time. If it is determined that the first operating parameter range includes the second operating parameter range, it means that the operating parameters of the current refrigeration plant are parameters that have appeared in the refrigeration-related plant as a standard reference object, so it is determined that the overall operation monitoring data of the current refrigeration plant matches the real-time monitoring data of the related plant. However, at present, it is only judged from the overall perspective, and it can only mean that the status of the current refrigeration unit at the current time node is normal, and it is impossible to determine whether there is a possibility of failure in the future, so further accurate judgment is required, that is, it is necessary to generate the associated equipment operation difference value based on the refrigeration-related calibration equipment and the current refrigeration plant.

[0124] In one embodiment, the calibrated refrigeration device is the first compressor in the current refrigeration plant, and the refrigeration-related calibration device is the second compressor in the refrigeration-related plant;

[0125] In step S300, generating an associated equipment operation difference value according to the refrigeration associated calibration equipment and the current refrigeration plant includes:

[0126] Step S321: applying a supervisory test excitation to the first compressor and the second compressor, and acquiring first vibration detection data collected by the first compressor at a preset reference position and second vibration detection data collected by the second compressor at a preset reference position, wherein the preset reference position is a cylinder body beside an exhaust valve of the first compressor and the second compressor;

[0127] Step S322: generating a first vibration information set according to the first vibration detection data, and generating a second vibration information set according to the second vibration detection data;

[0128] Step S323: acquiring first exhaust temperature data collected by the first compressor at a preset reference position and second exhaust temperature data collected by the second compressor at a preset reference position;

[0129] Step S324: calculating a first deviation value between the first exhaust temperature data and a preset average temperature, and calculating a second deviation value between the second exhaust temperature data and the preset average temperature, wherein the preset average temperature corresponds to the regulatory test stimulus;

[0130] In this step, the preset average temperature is based on the regulatory test stimulus, and multiple test units are pre-tested and temperature data are collected, and then the average of each temperature is calculated based on the collected temperature data. That is, after the normal equipment applies the regulatory test stimulus, the average temperature that can be detected by the cylinder body beside the exhaust valve is the preset average temperature. Then, the first deviation value and the second deviation value are calculated respectively to indicate the degree of deviation of the calibrated refrigeration equipment and the refrigeration-related calibration equipment from the normal temperature after the regulatory test stimulus is applied.

[0131] Furthermore, the first exhaust temperature data includes a plurality of collected temperatures Tc, and the specific formula for calculating the first deviation value is as follows:

[0132] ;

[0133] in, is the first deviation value, N is the number of collected temperatures, Tcx is the xth collected temperature, The preset average temperature.

[0134] The second deviation value is It indicates that the calculation method of the second deviation value is the same as that of the first deviation value, so it will not be repeated in this application.

[0135] Step S325: Generate an associated device operation difference value according to the first vibration information set, the second vibration information set, the first deviation value, and the second deviation value.

[0136] In this embodiment, a preset calibration position is pre-set, and the preset calibration position is a position where the compressor is more likely to be damaged. Specifically, by setting the preset calibration position on the cylinder body beside the exhaust valve of the compressor instead of setting it on the valve body, it is possible to obtain vibration information and temperature information on the one hand, and on the other hand, it is possible not to contact the valve body, so that the high temperature and high-frequency vibration generated by the valve body can be avoided from damaging the sensor. In addition, by first generating a first vibration information set based on the first vibration detection data, and generating a second vibration information set based on the second vibration detection data, and then obtaining the first exhaust temperature data collected by the first compressor at the preset calibration position and the second exhaust temperature data collected by the second compressor at the preset calibration position, it is possible to generate an associated device operation difference value. The associated device operation difference value is a numerical value indicating the difference in operating parameters between the refrigeration associated calibration device and the calibrated refrigeration equipment in the current refrigeration station during operation.

[0137] In one embodiment, the associated device operation difference value is generated based on the following formula:

[0138] ;

[0139] Among them, Rdv is the operating difference value of the associated equipment, is the vibration information weight, k is the number of cylinder vibration values ​​in the first vibration information set, Faj is the jth cylinder vibration value in the first vibration information set, is the mean value of the cylinder vibration value in the first vibration information set, Fbj is the jth cylinder vibration value in the second vibration information set, is the mean value of the cylinder vibration value in the second vibration information set, is the temperature information weight, is the first deviation value, is the second deviation value.

[0140] The vibration information weight and the temperature information weight are preset, and the sum of the two is 1. The vibration information weight and the temperature information weight respectively represent the proportion of vibration information and temperature information in measuring the operation difference between devices.

[0141] In this embodiment, the temperature and vibration data are combined to determine whether the compressor has a tendency to fail. Compared with the prior art, the standard range is set only by the historical data of previous equipment. However, different operating parameters may be easily caused due to different production batches and usage differences, which may lead to inaccurate set standard ranges. In this application, the operation of the refrigeration-related calibration equipment is used as a data reference template, which is equivalent to using the refrigeration data corresponding to the same batch of used equipment as a reference, thereby achieving accurate judgment and refrigeration abnormality supervision.

[0142] In one embodiment, in step S100, it is determined whether the current refrigeration plant is in an abnormal refrigeration state according to the refrigeration equipment operation data, and then the method further includes:

[0143] Step S021: If the judgment is no, a continuous refrigeration monitoring indication is generated, and the operation of the calibrated refrigeration equipment is monitored according to the continuous refrigeration monitoring indication.

[0144] Compared with the prior art that directly monitors all parts of the refrigeration system, which results in excessive consumption of monitoring resources and waste of resources, in this step, only the operating data of the refrigeration equipment is obtained, and when it is determined that the current refrigeration station is not in an abnormal refrigeration state, the full-scale refrigeration system monitoring is no longer performed. That is, a concept completely opposite to that in the prior art is adopted to monitor and judge refrigeration abnormalities, thereby realizing a resource-saving monitoring method.

[0145] In one embodiment, Figure 2 As shown, a refrigeration abnormality monitoring system for a refrigeration station is also provided, and the system comprises:

[0146] A refrigeration monitoring start module is used to obtain the refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration station, and determine whether the current refrigeration station is in an abnormal refrigeration state according to the refrigeration equipment operation data;

[0147] an associated device determination module, for obtaining a refrigeration plant association sequence of the current refrigeration plant if the determination is yes, and determining a refrigeration associated plant and a refrigeration associated calibration device according to the refrigeration plant association sequence;

[0148] An operation parameter comparison module is used to obtain the real-time monitoring data of the associated station of the refrigeration associated station, and determine whether the overall operation monitoring data of the current refrigeration station matches the real-time monitoring data of the associated station. If the determination is yes, an associated equipment operation difference value is generated according to the refrigeration associated calibration equipment and the current refrigeration station;

[0149] The supervision result generation module is used to determine whether the operation difference value of the associated equipment is less than or equal to a preset associated equipment difference threshold. If it is determined to be yes, a refrigeration fault prediction indication is generated, and the current refrigeration station is inspected and repaired according to the refrigeration fault prediction indication.

[0150] In one embodiment, the calibrated refrigeration equipment is a first compressor; the refrigeration monitoring startup module is also used to: obtain the refrigeration equipment operation data of the first compressor pre-calibrated in the current refrigeration station, perform data collection according to a preset power collection time point and obtain refrigeration collection point data, wherein one power collection time point corresponds to one refrigeration collection point data; generate the refrigeration operation load rate of the first compressor according to the refrigeration collection point data, wherein one refrigeration collection point data corresponds to one refrigeration operation load rate; filter out the refrigeration operation load rate within the refrigeration load rate calibration range, and record it as the overload load rate, wherein the refrigeration load rate calibration range is preset; calculate the overload interval time of adjacent overload load rates, and obtain The overload interval time is less than the overload time threshold and is recorded as a high-frequency time interval, wherein the number of the high-frequency time intervals is n, and one high-frequency time interval corresponds to two overload load rates; the mean of the two overload load rates corresponding to the high-frequency time interval is obtained and recorded as a first mean, wherein one high-frequency time interval corresponds to a first mean; an overload refrigeration fluctuation index is generated according to the overload load rate, the high-frequency time interval, the overload time threshold, and the first mean; it is determined whether the overload refrigeration fluctuation index is greater than or equal to the overload refrigeration fluctuation threshold; if it is determined to be yes, it is determined that the current refrigeration station is in a refrigeration abnormal state; if it is determined to be no, it is determined that the current refrigeration station is not in a refrigeration abnormal state.

[0151] In one embodiment, the refrigeration monitoring start module is further used to generate an overload refrigeration fluctuation index based on the following formula:

[0152] ;

[0153] Among them, Do is the index for generating overload cooling fluctuation, n is the number of high-frequency time intervals, ST is the overload time threshold, Tvi is the i-th high-frequency time interval, Ui is the first mean value corresponding to the i-th high-frequency time interval, and SU is the mean value of each overload load rate.

[0154] In one embodiment, the refrigeration plant association sequence includes multiple refrigeration plants of the same type, and each of the refrigeration plants of the same type is produced in the same batch as the current refrigeration plant; the associated equipment determination module is also used to: obtain the refrigeration use time of each refrigeration plant of the same type in the refrigeration plant association sequence, and record the refrigeration plant of the same type corresponding to the refrigeration use time greater than or equal to the refrigeration use calibration time as the first screening plant; extract the first screening plant equipment operating environment data of the first screening plant; extract the ambient temperature data, ambient humidity data and operating building insulation data from the first screening plant equipment operating environment data, and generate the ambient temperature range of the same type of plant, the ambient humidity range of the same type of plant and the building insulation range of the same type of plant ; Obtain the current station room environment data of the current refrigeration station room, and select the second screening station room from the first screening station room according to the current station room environment data, the environmental temperature range of the same type of station room, the environmental humidity range of the same type of station room and the thermal insulation range of the same type of station room building; Extract the same type of station room operation data of the second screening station room, and extract the refrigeration demand range of the second screening station room from the same type of station room operation data; Obtain the completed refrigeration demand of the current refrigeration station room, and generate a completed demand range according to the completed refrigeration demand; Set the second screening station room corresponding to the refrigeration demand range including the completed demand range as a refrigeration-associated station room, and set a refrigeration-associated calibration device according to the refrigeration-associated station room.

[0155] In one embodiment, the associated device determination module is further used to: extract current station room temperature data, current station room humidity data and current station room building insulation data from the current station room environment data. Then, according to the current station room temperature data, the current station room humidity data and the current station room building insulation data, the current station room environment temperature range, the current station room environment humidity range and the current station room building insulation range are generated respectively.

[0156] Among them, the maximum value and minimum value of the current station room ambient temperature range are the maximum value and minimum value in the current station room temperature data. The maximum value and minimum value of the current station room ambient humidity range are the maximum value and minimum value in the current station room humidity data. The current station room building insulation range is set according to the current station room building insulation data. Specifically, the current station room building insulation data includes the building main body where the current refrigeration station room is installed, and is mainly determined by the thickness of the building material of the building main body.

[0157] In one embodiment, the associated device determination module is further used to perform the following steps of setting the thermal insulation range of the current station building:

[0158] The current station building insulation data includes the thickness d of the building material. The thermal conductivity of the building material is represented by R, which can generate the insulation coefficient Ur.

[0159] The calculation formula of thermal insulation coefficient Ur is as follows:

[0160] .

[0161] Furthermore, a basic insulation fluctuation range is set, and the minimum and maximum values ​​of the range are represented by Umin and Umax respectively. The minimum and maximum values ​​of the current station building insulation range are Umin*Ur and Umax*Ur respectively.

[0162] In one embodiment, the associated device determination module is also used to: calculate the Hausdorff distance between the ambient temperature range of the same type of station building and the ambient temperature range of the current station building, recorded as the first Hausdorff distance; calculate the Hausdorff distance between the ambient humidity range of the same type of station building and the ambient humidity range of the current station building, recorded as the second Hausdorff distance; calculate the Hausdorff distance between the thermal insulation range of the same type of station building and the thermal insulation range of the current station building, recorded as the third Hausdorff distance. Then, the first standard distance, the second standard distance and the third standard distance are also preset.

[0163] The first screening station corresponding to the first Hausdorff distance being smaller than the first standard distance, the second Hausdorff distance being smaller than the second standard distance, and the third Hausdorff distance being smaller than the third standard distance is set as the second screening station.

[0164] In one embodiment, the operating parameter comparison module is also used to: obtain the real-time monitoring data of the associated station of the refrigeration associated station, and obtain the overall operating monitoring data of the current refrigeration station; extract the first operating parameter range from the real-time monitoring data of the associated station according to the preset station power, and extract the second operating parameter range from the overall operating monitoring data; determine whether the first operating parameter range contains the second operating parameter range; if the judgment is yes, determine that the overall operating monitoring data of the current refrigeration station matches the real-time monitoring data of the associated station; if the judgment is no, determine that the overall operating monitoring data of the current refrigeration station does not match the real-time monitoring data of the associated station.

[0165] In one embodiment, the calibrated refrigeration equipment is the first compressor in the current refrigeration plant, and the refrigeration-associated calibration equipment is the second compressor in the refrigeration-associated plant; the operating parameter comparison module is also used to: apply a regulatory test excitation to the first compressor and the second compressor, and obtain a first vibration detection data collected by the first compressor at a preset calibration position and a second vibration detection data collected by the second compressor at a preset calibration position, wherein the preset calibration position is the cylinder body beside the exhaust valve of the first compressor and the second compressor; generate a first vibration information set according to the first vibration detection data, and generate a second vibration information set according to the second vibration detection data; obtain the first exhaust temperature data collected by the first compressor at the preset calibration position and the second exhaust temperature data collected by the second compressor at the preset calibration position; calculate a first deviation value between the first exhaust temperature data and a preset average temperature, and calculate a second deviation value between the second exhaust temperature data and the preset average temperature, wherein the preset average temperature corresponds to the regulatory test excitation; generate an associated equipment operation difference value according to the first vibration information set, the second vibration information set, the first deviation value and the second deviation value.

[0166] In one embodiment, the operation parameter comparison module is further used to generate an associated device operation difference value based on the following formula:

[0167] ;

[0168] Among them, Rdv is the operating difference value of the associated equipment, is the vibration information weight, k is the number of cylinder vibration values ​​in the first vibration information set, Faj is the jth cylinder vibration value in the first vibration information set, is the mean value of the cylinder vibration value in the first vibration information set, Fbj is the jth cylinder vibration value in the second vibration information set, is the mean value of the cylinder vibration value in the second vibration information set, is the temperature information weight, is the first deviation value, is the second deviation value.

[0169] In one embodiment, the refrigeration monitoring start module is further used to: if the judgment is no, generate a refrigeration continuous monitoring indication, and perform operation monitoring on the calibrated refrigeration equipment according to the refrigeration continuous monitoring indication.

[0170] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps described in the above-mentioned refrigeration abnormality monitoring method for a refrigeration station when executing the computer program.

[0171] In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the steps described in the above-mentioned refrigeration abnormality monitoring method for a refrigeration station are implemented.

[0172] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0173] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0174] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for monitoring abnormal refrigeration in a refrigeration plant, characterized in that: The method comprises: Acquire the refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration station, and determine whether the current refrigeration station is in an abnormal refrigeration state according to the refrigeration equipment operation data; If the judgment is yes, then obtaining the refrigeration plant association sequence of the current refrigeration plant, and determining the refrigeration associated plant and the refrigeration associated calibration equipment according to the refrigeration plant association sequence; Acquire the associated station real-time monitoring data of the refrigeration associated station, and determine whether the overall operation monitoring data of the current refrigeration station matches the associated station real-time monitoring data, and if so, generate an associated equipment operation difference value according to the refrigeration associated calibration device and the current refrigeration station; It is determined whether the associated equipment operation difference value is less than or equal to a preset associated equipment difference threshold value. If it is determined to be yes, a refrigeration fault prediction indication is generated, and the current refrigeration plant is inspected and repaired according to the refrigeration fault prediction indication.

2. The method for monitoring abnormal refrigeration in a refrigeration plant according to claim 1, characterized in that: The standardized refrigeration device is a first compressor; Acquiring refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration station, and judging whether the current refrigeration station is in an abnormal refrigeration state according to the refrigeration equipment operation data, including: Acquire the refrigeration equipment operation data of the first compressor pre-calibrated in the current refrigeration station, collect data according to the preset power collection time point and obtain the refrigeration collection point data, wherein one power collection time point corresponds to one refrigeration collection point data; Generate a refrigeration operation load rate of the first compressor according to the refrigeration collection point data, wherein one refrigeration collection point data corresponds to one refrigeration operation load rate; Screening out the refrigeration operation load rate within the refrigeration load rate calibration range and recording it as the overload load rate, wherein the refrigeration load rate calibration range is preset; Calculate the overload intervals of adjacent overload load rates, obtain the overload intervals that are less than the overload time threshold, and record them as high-frequency time intervals, wherein the number of the high-frequency time intervals is n, and one high-frequency time interval corresponds to two overload load rates; Obtaining the average of two overload load rates corresponding to the high-frequency time interval and recording it as a first average, wherein one high-frequency time interval corresponds to one first average; generating an overload cooling fluctuation index according to the overload load rate, the high frequency time interval, the overload time threshold, and the first mean value; Determining whether the overload cooling fluctuation index is greater than or equal to the overload cooling fluctuation threshold; If the judgment is yes, then it is judged that the current refrigeration station is in an abnormal refrigeration state; If the judgment is no, it is determined that the current refrigeration station is not in an abnormal refrigeration state.

3. The method for monitoring abnormal refrigeration in a refrigeration plant according to claim 2, characterized in that: The overload cooling fluctuation index is generated based on the following formula: ； Among them, Do is the index for generating overload cooling fluctuation, n is the number of high-frequency time intervals, ST is the overload time threshold, Tvi is the i-th high-frequency time interval, Ui is the first mean value corresponding to the i-th high-frequency time interval, and SU is the mean value of each overload load rate.

4. The method for monitoring abnormal refrigeration in a refrigeration plant according to claim 1, characterized in that: The refrigeration plant association sequence includes multiple refrigeration plants of the same type, and each of the refrigeration plants of the same type is produced in the same batch as the current refrigeration plant; Determining a refrigeration-related station and a refrigeration-related calibration device according to the refrigeration station association sequence includes: Obtaining the refrigeration usage time of each refrigeration room of the same type in the refrigeration room association sequence, and recording the refrigeration room of the same type corresponding to the refrigeration usage time greater than or equal to the refrigeration usage calibration time as the first screening room; Extracting the first screening station equipment operating environment data of the first screening station; Extracting ambient temperature data, ambient humidity data and operating building insulation data from the first screening station equipment operating environment data, and generating the ambient temperature range, ambient humidity range and building insulation range of the same type of station; Acquire current station building environmental data of the current refrigeration station building, and select a second screening station building from the first screening station building according to the current station building environmental data, the environmental temperature range of the same type of station building, the environmental humidity range of the same type of station building, and the thermal insulation range of the same type of station building; Extracting operation data of a same-type station building of the second screening station building, and extracting a refrigeration demand range of the second screening station building from the operation data of the same-type station building; Acquire the completed refrigeration demand of the current refrigeration plant, and generate a completed demand range according to the completed refrigeration demand; The second screening station corresponding to the refrigeration demand range including the completed demand range is set as a refrigeration-related station, and a refrigeration-related calibration device is set according to the refrigeration-related station.

5. The method for monitoring abnormal refrigeration in a refrigeration plant according to claim 1, characterized in that: Acquiring the real-time monitoring data of the associated station of the refrigeration associated station, and judging whether the overall operation monitoring data of the current refrigeration station matches the real-time monitoring data of the associated station, including: Acquire the real-time monitoring data of the associated station of the refrigeration associated station, and acquire the overall operation monitoring data of the current refrigeration station; Extracting a first operating parameter range from the real-time monitoring data of the associated station building according to the preset station building power, and extracting a second operating parameter range from the overall operation monitoring data; determining whether the first operating parameter range includes the second operating parameter range; If the judgment is yes, then judging whether the overall operation monitoring data of the current refrigeration plant matches the real-time monitoring data of the associated plant; If the judgment is no, it is determined that the overall operation monitoring data of the current refrigeration plant does not match the real-time monitoring data of the associated plant.

6. The method for monitoring abnormal refrigeration in a refrigeration plant according to claim 1, characterized in that: The calibrated refrigeration equipment is the first compressor in the current refrigeration plant, and the refrigeration-related calibration equipment is the second compressor in the refrigeration-related plant; Generate an associated equipment operation difference value according to the refrigeration associated calibration equipment and the current refrigeration plant, including: Applying a supervisory test excitation to the first compressor and the second compressor, and acquiring first vibration detection data collected by the first compressor at a preset reference position and second vibration detection data collected by the second compressor at a preset reference position, wherein the preset reference position is a cylinder body beside an exhaust valve of the first compressor and the second compressor; generating a first vibration information set according to the first vibration detection data, and generating a second vibration information set according to the second vibration detection data; Acquire first exhaust temperature data collected by the first compressor at a preset reference position and second exhaust temperature data collected by the second compressor at a preset reference position; calculating a first deviation value between the first exhaust temperature data and a preset average temperature, and calculating a second deviation value between the second exhaust temperature data and the preset average temperature, wherein the preset average temperature corresponds to the regulatory test stimulus; An associated equipment operation difference value is generated according to the first vibration information set, the second vibration information set, the first deviation value, and the second deviation value.

7. The method for monitoring abnormal refrigeration in a refrigeration plant according to claim 6, characterized in that: The associated equipment operation variance value is generated based on the following formula: ； Among them, Rdv is the operating difference value of the associated equipment, is the vibration information weight, k is the number of cylinder vibration values ​​in the first vibration information set, Faj is the jth cylinder vibration value in the first vibration information set, is the mean value of the cylinder vibration value in the first vibration information set, Fbj is the jth cylinder vibration value in the second vibration information set, is the mean value of the cylinder vibration value in the second vibration information set, is the temperature information weight, is the first deviation value, is the second deviation value.

8. A refrigeration abnormality monitoring system for a refrigeration station, characterized in that: The system comprises: A refrigeration monitoring start module is used to obtain the refrigeration equipment operation data of the marked refrigeration equipment in the current refrigeration station, and determine whether the current refrigeration station is in an abnormal refrigeration state according to the refrigeration equipment operation data; an associated device determination module, for obtaining a refrigeration plant association sequence of the current refrigeration plant if the determination is yes, and determining a refrigeration associated plant and a refrigeration associated calibration device according to the refrigeration plant association sequence; An operation parameter comparison module is used to obtain the real-time monitoring data of the associated station of the refrigeration associated station, and determine whether the overall operation monitoring data of the current refrigeration station matches the real-time monitoring data of the associated station. If the determination is yes, an associated equipment operation difference value is generated according to the refrigeration associated calibration equipment and the current refrigeration station; The supervision result generation module is used to determine whether the operation difference value of the associated equipment is less than or equal to a preset associated equipment difference threshold. If it is determined to be yes, a refrigeration fault prediction indication is generated, and the current refrigeration station is inspected and repaired according to the refrigeration fault prediction indication.

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