Energy consumption equipment consumption monitoring and abnormity alarm system based on data acquisition and analysis

Abstract

The invention belongs to the field of energy consumption monitoring, relates to a data analysis technology, is used for solving the problem that the overall energy consumption state cannot be evaluated by combining energy conversion and cluster energy consumption analysis in the prior art, and particularly relates to an energy consumption equipment consumption monitoring and abnormity alarm system based on data acquisition and analysis, which comprises a monitoring alarm platform, the monitoring alarm platform is in communication connection with a usage monitoring module, a unit evaluation module, an optimization analysis module and a database. The consumption monitoring module is used for monitoring and analyzing the energy consumption of the energy consumption equipment: generating a monitoring period, marking the energy consumption equipment as a monitoring object, acquiring an energy consumption value of the monitoring object in the monitoring period, and marking the monitoring object as a normal object or an abnormal object according to the energy consumption value; the energy consumption of the energy consumption equipment can be monitored and analyzed, then different types of energy consumption are converted to obtain the final energy consumption value, and the energy consumption state of the energy consumption equipment is fed back and evaluated according to the energy consumption value.

Description

Technical Field

[0001] The present invention belongs to the field of energy consumption monitoring and relates to data analysis technology, in particular to an energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis. Background Art

[0002] Energy consumption monitoring systems generally use automation and information technology to achieve online collection, calculation, analysis and processing of energy data, including centralized collection, statistics and analysis of electricity, water, gas, coal, oil, heat and other energy sources. The system can monitor the consumption of various types of energy in the enterprise in real time, and help enterprises strengthen energy management through data analysis, mining and trend analysis.

[0003] The invention patent with announcement number CN117196351B discloses an intelligent building energy consumption monitoring method and system based on the Internet of Things. The energy consumption monitoring method determines the necessity of energy consumption monitoring of energy-consuming equipment by monitoring priorities of energy-consuming equipment in other areas and the deviation of energy consumption data of the same type of energy-consuming equipment inside the building, and determines the use of a unified Internet of Things monitoring terminal or a separate Internet of Things monitoring terminal for energy-consuming equipment based on the necessity of energy consumption monitoring, thereby improving the processing efficiency of energy consumption monitoring data; however, the energy consumption monitoring method cannot combine energy conversion and cluster energy consumption analysis to evaluate the overall energy consumption status, nor can it analyze the actual energy consumption status of energy-consuming equipment through production and consumption balance analysis, resulting in the accuracy of the energy consumption monitoring results cannot be guaranteed.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide an energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis, which is used to solve the problem that the existing technology cannot combine energy conversion and cluster energy consumption analysis to evaluate the overall energy consumption status; The technical problem to be solved by the present invention is: how to provide an energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis that can combine energy conversion and cluster energy consumption analysis to evaluate the overall energy consumption status.

[0006] The purpose of the present invention can be achieved by the following technical solutions: An energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis includes a monitoring and alarm platform, wherein the monitoring and alarm platform is communicatively connected to a usage monitoring module, a unit evaluation module, an optimization analysis module, and a database; The usage monitoring module is used to monitor and analyze the energy consumption of energy-consuming equipment: generate a monitoring cycle, mark the energy-consuming equipment as a monitoring object, obtain the energy consumption value of the monitoring object within the monitoring cycle, and mark the monitoring object as a normal object or an abnormal object according to the energy consumption value; The unit evaluation module is used to perform overall energy consumption evaluation and analysis on the units of energy-consuming equipment: an energy consumption cluster is constructed from all monitoring objects in the same unit, and the ratio of the number of abnormal objects in the energy consumption cluster to the number of monitoring objects is marked as the abnormal coefficient of the energy consumption cluster. Whether the overall energy consumption state of the energy consumption cluster meets the requirements is determined by the abnormal coefficient. If the requirements are met, the inspection object is marked, and if the requirements are not met, the energy consumption cluster is subjected to production and consumption balance analysis; The optimization analysis module is used to perform decision analysis on the optimization direction of the inspection object: mark the difference between the energy consumption value of the inspection object in the current monitoring period and the energy consumption threshold as the energy consumption performance value NB of the inspection object, obtain the type compliance coefficient LF of the inspection object, and obtain the fault coefficient GZ of the inspection object by numerically calculating the energy consumption performance value NB and the type compliance coefficient LF; and determine whether the inspection object has an operating fault through the fault coefficient GZ.

[0007] Furthermore, the process of obtaining the energy consumption value of the monitored object includes: obtaining the electricity consumption, oil consumption, gas consumption, coal consumption and water consumption of the monitored object during the monitoring period, calculating the oil consumption, gas consumption, coal consumption and water consumption according to the conversion efficiency of the corresponding generator to obtain the oil consumption power generation, gas consumption power generation, coal consumption power generation and water consumption power generation, and marking the sum of the electricity consumption, oil consumption power generation, gas consumption power generation, coal consumption power generation and water consumption power generation as the energy consumption value of the monitored object during the monitoring period.

[0008] Furthermore, the specific process of marking the monitored object as a normal object or an abnormal object includes: obtaining the energy consumption threshold of the monitored object through the database, and comparing the energy consumption value of the monitored object during the monitoring period with the energy consumption threshold: if the energy consumption value is less than the energy consumption threshold, it is determined that the energy consumption status of the monitored object during the monitoring period meets the requirements, and the corresponding monitored object is marked as a normal object; if the energy consumption value is greater than or equal to the energy consumption threshold, it is determined that the energy consumption status of the monitored object during the monitoring period does not meet the requirements, and the corresponding monitored object is marked as an abnormal object.

[0009] Furthermore, the specific process of determining whether the overall energy consumption status of the energy consumption cluster meets the requirements includes: obtaining the abnormal threshold through the database, and comparing the abnormal coefficient with the abnormal threshold: if the abnormal coefficient is less than the abnormal threshold, then it is determined that the overall energy consumption status of the energy consumption cluster meets the requirements, and the abnormal objects in the energy consumption cluster are marked as inspection objects, and an optimization analysis signal is generated and the optimization analysis signal and the inspection object are sent to the optimization analysis module through the monitoring and alarm platform; if the abnormal coefficient is greater than or equal to the abnormal threshold, then it is determined that the overall energy consumption status of the energy consumption cluster does not meet the requirements.

[0010] Furthermore, the specific process of conducting production and consumption balance analysis on the energy consumption cluster includes: marking the sum of the energy consumption values ​​of all monitored objects in the energy consumption cluster as the energy consumption analysis value, marking the ratio of the energy consumption analysis value to the total output value of the energy consumption cluster during the monitoring period as the balance coefficient, obtaining the balance threshold through the database, and comparing the balance coefficient with the balance threshold: if the balance coefficient is less than the balance threshold, it is determined that the overall energy consumption status of the energy consumption cluster is affected by the production capacity; if the balance coefficient is greater than or equal to the balance threshold, it is determined that the overall energy consumption of the energy consumption cluster is affected by the equipment operation, generating a unit alarm signal and sending the unit alarm signal to the mobile terminal of the manager through the monitoring alarm platform.

[0011] Furthermore, the process of obtaining the type compliance coefficient LF includes: arranging the energy types of the inspection object in the current monitoring period in order from high to low according to the corresponding power consumption or power generation to obtain a type analysis sequence, marking the most recent L1 monitoring periods as comparison periods, obtaining the energy consumption value of the inspection object in the comparison period and the total output value of the energy consumption cluster to which it belongs, marking the ratio of the energy consumption value to the total output value of the energy consumption cluster to which it belongs as the comparison priority value of the comparison period, marking the comparison period with the smallest comparison priority value as the extraction period of the inspection object, arranging the energy types of the inspection object in the comparison period in order from high to low according to the corresponding power consumption or power generation to obtain a type comparison sequence, marking the absolute value of the difference between the sequence number of the energy type in the type analysis sequence and the sequence number in the type comparison sequence as the compliance value of the energy type, and summing and averaging the compliance values ​​of all energy types to obtain the type compliance coefficient LF of the inspection object.

[0012] Furthermore, the specific process of determining whether the inspection object has an operational fault includes: obtaining the fault threshold GZmax through the database, and comparing the fault coefficient GZ with the fault threshold GZmax: if the fault coefficient GZ is less than the fault threshold GZmax, it is determined that the inspection object does not have an operational fault, and a supervision optimization signal is generated and sent to the mobile phone terminal of the management personnel through the monitoring alarm platform; if the fault coefficient GZ is greater than or equal to the fault threshold GZmax, it is determined that the inspection object has an operational fault, and a device alarm signal is generated and sent to the mobile phone terminal of the management personnel through the monitoring alarm platform.

[0013] The present invention has the following beneficial effects: 1. The energy consumption of energy-consuming equipment can be monitored and analyzed through the usage monitoring module. The energy consumption of various types of energy-consuming equipment can be counted in a periodic monitoring manner, and then different types of energy consumption can be converted to obtain the final energy consumption value. The energy consumption status of energy-consuming equipment can be fed back and evaluated based on the energy consumption value; 2. The unit evaluation module can be used to conduct overall energy consumption evaluation and analysis on the units of energy-consuming equipment, and provide feedback on the overall energy consumption status based on the differentiated marking results of all energy-consuming equipment in the unit. When the overall energy consumption status is abnormal, a production and consumption balance analysis is performed to obtain the balance coefficient, and the actual energy consumption status of the energy consumption cluster is evaluated through the balance coefficient; 3. The optimization analysis module can be used to make decision analysis on the optimization direction of the inspection object, and the energy consumption performance value and type compliance coefficient of the inspection object can be combined for comprehensive analysis and calculation to obtain the fault coefficient. The operating failure probability of the energy-consuming equipment can be analyzed according to the fault coefficient, and then the optimization direction of the inspection object can be marked; the accuracy and optimization efficiency of the energy consumption monitoring results can be improved by independent statistics - overall evaluation - individual optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1 is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0016] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1: Figure 1 As shown, the energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis includes a monitoring and alarm platform, and the monitoring and alarm platform is communicatively connected with a usage monitoring module, a unit evaluation module, an optimization analysis module and a database.

[0018] The usage monitoring module is used to monitor and analyze the energy consumption of energy-consuming equipment: generate a monitoring cycle, mark the energy-consuming equipment as a monitoring object, obtain the power consumption, oil consumption, gas consumption, coal consumption and water consumption of the monitoring object in the monitoring cycle, calculate the oil consumption, gas consumption, coal consumption and water consumption according to the conversion efficiency of the corresponding generator to obtain the oil consumption power generation, gas consumption power generation, coal consumption power generation and water consumption power generation. For example, the conversion efficiency of the fuel generator is generally between 20% and 50%, so the oil consumption power generation corresponds to the conversion efficiency of the fuel generator using 35% for conversion calculation, mark the sum of the power consumption, oil consumption power generation, gas consumption power generation, coal consumption power generation and water consumption power generation as the energy consumption value of the monitoring object in the monitoring cycle, obtain the energy consumption threshold of the monitoring object through the database, and compare the energy consumption value of the monitoring object in the monitoring cycle with the energy consumption threshold: If the energy consumption value is less than the energy consumption threshold, it is determined that the energy consumption state of the monitored object during the monitoring period meets the requirements, and the corresponding monitored object is marked as a normal object; If the energy consumption value is greater than or equal to the energy consumption threshold, it is determined that the energy consumption status of the monitored object during the monitoring period does not meet the requirements, and the corresponding monitored object is marked as an abnormal object; the various types of energy consumption of energy-consuming equipment are counted in a periodic monitoring manner, and then the different types of energy consumption are converted to obtain the final energy consumption value, and the energy consumption status of the energy-consuming equipment is fed back and evaluated based on the energy consumption value.

[0019] The unit evaluation module is used to conduct overall energy consumption evaluation and analysis on the units of energy-consuming equipment: an energy consumption cluster is constructed from all monitoring objects in the same unit, and the ratio of the number of abnormal objects in the energy consumption cluster to the number of monitoring objects is marked as the abnormal coefficient of the energy consumption cluster. The abnormal threshold is obtained through the database, and the abnormal coefficient is compared with the abnormal threshold: If the abnormal coefficient is less than the abnormal threshold, the overall energy consumption status of the energy consumption cluster is determined to meet the requirements, the abnormal objects in the energy consumption cluster are marked as investigation objects, an optimization analysis signal is generated, and the optimization analysis signal and the investigation object are sent to the optimization analysis module through the monitoring and alarm platform; If the abnormal coefficient is greater than or equal to the abnormal threshold, it is determined that the overall energy consumption state of the energy consumption cluster does not meet the requirements, and the energy consumption cluster is subjected to production and consumption balance analysis: the sum of the energy consumption values ​​of all monitored objects in the energy consumption cluster is marked as the energy consumption analysis value, and the ratio of the energy consumption analysis value to the total output value of the energy consumption cluster during the monitoring period is marked as the balance coefficient. The balance threshold is obtained through the database, and the balance coefficient is compared with the balance threshold: If the balancing coefficient is less than the balancing threshold, it is determined that the overall energy consumption status of the energy consumption cluster is affected by the production capacity; If the balancing coefficient is greater than or equal to the balancing threshold, it is determined that the overall energy consumption of the energy consumption cluster is affected by the operation of the equipment, and a unit alarm signal is generated and sent to the mobile terminal of the manager through the monitoring alarm platform; the differentiated marking results of all energy-consuming equipment in the unit are integrated to provide feedback on the overall energy consumption status, and when the overall energy consumption status is abnormal, a production and consumption balance analysis is performed to obtain the balancing coefficient, and the actual energy consumption status of the energy consumption cluster is evaluated through the balancing coefficient.

[0020] The optimization analysis module is used to make decision analysis on the optimization direction of the inspection object: the difference between the energy consumption value of the inspection object in the current monitoring period and the energy consumption threshold is marked as the energy consumption performance value NB of the inspection object, and the energy types of the inspection object in the current monitoring period are arranged in descending order according to the corresponding power consumption or power generation to obtain a type analysis sequence. The energy types include electricity, fuel oil, gas, coal and water. The most recent L1 monitoring period is marked as a comparison period, and the energy consumption value of the inspection object in the comparison period and the total output value of the energy consumption cluster to which it belongs are obtained. The ratio of the value to the total output value of the energy consumption cluster to which it belongs is marked as the comparison priority value of the comparison period, the comparison period with the smallest comparison priority value is marked as the extraction period of the inspection object, the energy types of the inspection object in the comparison period are arranged in descending order according to the corresponding power consumption or power generation to obtain a type comparison sequence, the absolute value of the difference between the sequence number of the energy type in the type analysis sequence and the sequence number in the type comparison sequence is marked as the compliance value of the energy type, and the compliance values ​​of all energy types are summed and averaged to obtain the type compliance coefficient LF of the inspection object.

[0021] The fault coefficient GZ of the object to be checked is obtained by the formula GZ=k1×NB+k2×LF, where k1 and k2 are both proportional coefficients, and k1>k2>1; the fault threshold GZmax is obtained through the database, and the fault coefficient GZ is compared with the fault threshold GZmax: If the fault coefficient GZ is less than the fault threshold GZmax, it is determined that the object under investigation does not have an operating fault, and a supervision optimization signal is generated and sent to the mobile terminal of the manager through the monitoring alarm platform; If the fault coefficient GZ is greater than or equal to the fault threshold GZmax, it is determined that the object under investigation has an operating fault, and an equipment alarm signal is generated and sent to the manager's mobile terminal through the monitoring alarm platform; the energy consumption performance value and type compliance coefficient of the object under investigation are comprehensively analyzed and calculated to obtain the fault coefficient, and the operating failure probability of the energy-consuming equipment is analyzed according to the fault coefficient, and then the optimization direction of the object under investigation is marked; the accuracy and optimization efficiency of the energy consumption monitoring results are improved by independent statistics-overall evaluation-individual optimization.

[0022] Embodiment 2: Figure 2 As shown, the energy consumption equipment usage monitoring and abnormal alarm method based on data collection and analysis includes the following steps: Step 1: Monitor and analyze the energy consumption of energy-consuming equipment: generate a monitoring cycle, mark the energy-consuming equipment as a monitoring object, obtain the energy consumption value of the monitoring object within the monitoring cycle, and mark the monitoring object as a normal object or an abnormal object based on the energy consumption value; Step 2: Conduct overall energy consumption assessment and analysis on the units of energy-consuming equipment: construct an energy consumption cluster from all monitoring objects in the same unit, obtain the abnormal coefficient of the energy consumption cluster, and determine whether the overall energy consumption status of the energy consumption cluster meets the requirements based on the abnormal coefficient. If it does not meet the requirements, conduct production and consumption balance analysis on the energy consumption cluster; Step 3: Conduct decision analysis on the optimization direction of the inspection object: obtain the energy consumption performance value NB and the type compliance coefficient LF of the inspection object and perform numerical calculation to obtain the fault coefficient GZ. Use the fault coefficient GZ to determine whether the inspection object has an operating fault.

[0023] The energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis generates a monitoring cycle when working, marks the energy consumption equipment as the monitoring object, obtains the energy consumption value of the monitoring object within the monitoring cycle, and marks the monitoring object as a normal object or an abnormal object according to the energy consumption value; constructs an energy consumption cluster from all the monitoring objects in the same unit, obtains the abnormal coefficient of the energy consumption cluster, and determines whether the overall energy consumption status of the energy consumption cluster meets the requirements based on the abnormal coefficient. If it does not meet the requirements, the energy consumption balance analysis of the energy consumption cluster is performed; obtains the energy consumption performance value NB and the type compliance coefficient LF of the inspection object and performs numerical calculations to obtain the fault coefficient GZ, and determines whether the inspection object has an operating fault through the fault coefficient GZ.

[0024] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0025] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula GZ=k1×NB+k2×LF; technicians in this field collect multiple groups of sample data and set corresponding fault coefficients for each group of sample data; substitute the set fault coefficients and the collected sample data into the formula, any two formulas constitute a set of two-variable linear equations, screen the calculated coefficients and take the average, and obtain the values ​​of k1 and k2 as 2.85 and 2.03 respectively; The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding fault coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the fault coefficient is proportional to the energy consumption performance value.

[0026] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0027] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. Energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis, characterized by: It includes a monitoring and alarm platform, which is communicatively connected to a usage monitoring module, a unit evaluation module, an optimization analysis module and a database; The usage monitoring module is used to monitor and analyze the energy consumption of energy-consuming equipment: generate a monitoring cycle, mark the energy-consuming equipment as a monitoring object, obtain the energy consumption value of the monitoring object within the monitoring cycle, and mark the monitoring object as a normal object or an abnormal object according to the energy consumption value; The unit evaluation module is used to perform overall energy consumption evaluation and analysis on the units of energy-consuming equipment: an energy consumption cluster is constructed from all monitoring objects in the same unit, and the ratio of the number of abnormal objects in the energy consumption cluster to the number of monitoring objects is marked as the abnormal coefficient of the energy consumption cluster. Whether the overall energy consumption state of the energy consumption cluster meets the requirements is determined by the abnormal coefficient. If the requirements are met, the inspection object is marked, and if the requirements are not met, the energy consumption cluster is subjected to production and consumption balance analysis; The optimization analysis module is used to perform decision analysis on the optimization direction of the inspection object: mark the difference between the energy consumption value of the inspection object in the current monitoring period and the energy consumption threshold as the energy consumption performance value NB of the inspection object, obtain the type compliance coefficient LF of the inspection object, and obtain the fault coefficient GZ of the inspection object by numerically calculating the energy consumption performance value NB and the type compliance coefficient LF; and determine whether the inspection object has an operating fault through the fault coefficient GZ.

2. The energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis according to claim 1 is characterized in that: The process of obtaining the energy consumption value of the monitored object includes: obtaining the electricity consumption, oil consumption, gas consumption, coal consumption and water consumption of the monitored object during the monitoring period, calculating the oil consumption, gas consumption, coal consumption and water consumption according to the conversion efficiency of the corresponding generator to obtain the oil consumption power generation, gas consumption power generation, coal consumption power generation and water consumption power generation, and marking the sum of the electricity consumption, oil consumption power generation, gas consumption power generation, coal consumption power generation and water consumption power generation as the energy consumption value of the monitored object during the monitoring period.

3. The energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis according to claim 2 is characterized in that: The specific process of marking a monitored object as a normal object or an abnormal object includes: obtaining the energy consumption threshold of the monitored object through the database, and comparing the energy consumption value of the monitored object during the monitoring period with the energy consumption threshold: if the energy consumption value is less than the energy consumption threshold, it is determined that the energy consumption status of the monitored object during the monitoring period meets the requirements, and the corresponding monitored object is marked as a normal object; if the energy consumption value is greater than or equal to the energy consumption threshold, it is determined that the energy consumption status of the monitored object during the monitoring period does not meet the requirements, and the corresponding monitored object is marked as an abnormal object.

4. The energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis according to claim 3 is characterized in that: The specific process of determining whether the overall energy consumption status of the energy consumption cluster meets the requirements includes: obtaining the abnormal threshold through the database, and comparing the abnormal coefficient with the abnormal threshold: if the abnormal coefficient is less than the abnormal threshold, it is determined that the overall energy consumption status of the energy consumption cluster meets the requirements, and the abnormal objects in the energy consumption cluster are marked as inspection objects, and an optimization analysis signal is generated and the optimization analysis signal and the inspection object are sent to the optimization analysis module through the monitoring and alarm platform; if the abnormal coefficient is greater than or equal to the abnormal threshold, it is determined that the overall energy consumption status of the energy consumption cluster does not meet the requirements.

5. The energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis according to claim 4 is characterized in that: The specific process of conducting production and consumption balance analysis on energy consumption clusters includes: marking the sum of the energy consumption values ​​of all monitored objects in the energy consumption cluster as the energy consumption analysis value, marking the ratio of the energy consumption analysis value to the total output value of the energy consumption cluster during the monitoring period as the balance coefficient, obtaining the balance threshold through the database, and comparing the balance coefficient with the balance threshold: if the balance coefficient is less than the balance threshold, it is determined that the overall energy consumption status of the energy consumption cluster is affected by the production capacity; if the balance coefficient is greater than or equal to the balance threshold, it is determined that the overall energy consumption of the energy consumption cluster is affected by the operation of the equipment, generating a unit alarm signal and sending the unit alarm signal to the mobile terminal of the manager through the monitoring alarm platform.

6. The energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis according to claim 5 is characterized in that: The process of obtaining the type compliance coefficient LF includes: arranging the energy types of the inspection object in the current monitoring period in order from high to low according to the corresponding power consumption or power generation to obtain a type analysis sequence, marking the most recent L1 monitoring periods as comparison periods, obtaining the energy consumption value of the inspection object in the comparison period and the total output value of the energy consumption cluster to which it belongs, marking the ratio of the energy consumption value to the total output value of the energy consumption cluster to which it belongs as the comparison priority value of the comparison period, marking the comparison period with the smallest comparison priority value as the extraction period of the inspection object, arranging the energy types of the inspection object in the comparison period in order from high to low according to the corresponding power consumption or power generation to obtain a type comparison sequence, marking the absolute value of the difference between the sequence number of the energy type in the type analysis sequence and the sequence number in the type comparison sequence as the compliance value of the energy type, and summing and averaging the compliance values ​​of all energy types to obtain the type compliance coefficient LF of the inspection object.

7. The energy consumption equipment usage monitoring and abnormal alarm system based on data collection and analysis according to claim 6 is characterized in that: The specific process of determining whether the inspection object has an operational fault includes: obtaining the fault threshold GZmax through the database, and comparing the fault coefficient GZ with the fault threshold GZmax: if the fault coefficient GZ is less than the fault threshold GZmax, it is determined that the inspection object does not have an operational fault, and a supervision optimization signal is generated and sent to the mobile phone terminal of the manager through the monitoring alarm platform; if the fault coefficient GZ is greater than or equal to the fault threshold GZmax, it is determined that the inspection object has an operational fault, and a device alarm signal is generated and sent to the mobile phone terminal of the manager through the monitoring alarm platform.

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