Intelligent warehouse management system based on data processing technology

Abstract

The invention relates to the field of warehouse management, in particular to an intelligent warehouse management system based on a data processing technology, which comprises an environment management and control center, a data acquisition unit, a monitoring judgment unit, an internal cause fault screening unit, an external cause interference elimination unit, a regulation and control analysis unit and an alarm unit. According to the invention, the internal cause fault screening unit is mainly used for monitoring the fluctuation of the ventilation air speed of the intelligent warehouse so as to analyze the operation fault of the intelligent warehouse, and whether the air duct air speed value exceeds the preset threshold value or not is used as a judgment basis for judging whether the internal ventilation and heat dissipation of the intelligent warehouse has the operation fault or not. If a part operation fault signal is judged and generated, accurate screening is realized to quickly carry out corresponding maintenance or cleaning links; if a part operation normal signal is generated and then an external interference elimination unit is combined, the internal fault factor judgment accuracy is improved, and meanwhile, the ventilation and heat dissipation effect in the intelligent warehouse is adjusted in real time according to external interference factors in a targeted mode.

Description

Technical Field

[0001] The present invention relates to the field of warehouse management, and in particular to an intelligent warehouse management system based on data processing technology. Background Art

[0002] In the field of warehouse management, with the continuous advancement of intelligent technology, intelligent warehouse systems have gradually become a new trend in the development of the industry. However, in actual applications, intelligent warehouse systems face many challenges. For example, in terms of environmental control, traditional warehouse management systems often rely on manual monitoring and maintenance, which is not only inefficient, but also difficult to achieve real-time monitoring and precise control of the internal warehouse environment. In a high-temperature environment, can the interior of the warehouse be adaptively and efficiently ventilated and cooled to improve the quality and safety of stored items, and avoid external environmental factors that interfere with the self-inspection of internal equipment, resulting in untimely and inaccurate warnings for internal operating components, and whether the purpose of energy saving can be achieved in a low-temperature environment? Therefore, how to achieve automatic monitoring, fault warning and precise control of intelligent warehouse systems has become an urgent problem to be solved;

[0003] In response to the above technical problems, this application proposes a solution. Summary of the Invention

[0004] In the present invention, the internal fault screening unit is mainly used to monitor the fluctuation of the intelligent warehouse ventilation wind speed to analyze the operational faults of the intelligent warehouse. Whether the duct wind speed value exceeds the preset threshold is used as the basis for judging whether there is an operational fault in the ventilation and heat dissipation inside the intelligent warehouse. If the judgment generates a component operation fault signal, accurate screening is achieved to quickly carry out the corresponding maintenance or cleaning link; if the component operation normal signal is generated and combined with the external interference elimination unit, while improving the accuracy of the internal fault factor judgment, the internal ventilation and heat dissipation effect of the intelligent warehouse is adjusted in real time according to the external interference factors, achieving effective heat dissipation in high temperature weather and energy-saving effect of low temperature heat dissipation, and proposing an intelligent warehouse management system based on data processing technology.

[0005] The object of the present invention can be achieved by the following technical solutions: an intelligent warehouse management system based on data processing technology, comprising an environment control center, a data acquisition unit, a monitoring and evaluation unit, an internal fault screening unit, an external interference elimination unit, a control and analysis unit, and an alarm unit;

[0006] The environmental control center generates an operation fault determination instruction and sends the operation fault determination instruction to the data acquisition unit. The data acquisition unit is used to collect abnormal risk values and abnormal interference factor values inside the warehouse. The abnormal interference factor values include internal fault factor values and external interference factor values, and transmit the abnormal risk values, internal fault factor values and external interference factor values to the monitoring and evaluation unit, the internal fault screening unit, and the external interference elimination unit respectively;

[0007] The monitoring and evaluation unit receives the abnormal risk value, monitors and analyzes the abnormal risk value, and sends the acquired operation fault signal to the internal fault screening unit and the alarm unit;

[0008] The internal fault screening unit receives the operation fault signal, evaluates and analyzes the internal fault, and sends the obtained component operation fault signal to the control and analysis unit;

[0009] The external interference elimination unit receives the external interference factor value, evaluates and eliminates the external interference factor value, and sends the obtained operation adjustment signal to the control analysis unit;

[0010] The control and analysis unit receives component operation fault signals and operation adjustment signals, generates a cleaning signal or a wind speed adjustment signal, and sends the cleaning signal or the wind speed adjustment signal to the environmental control center to match the corresponding maintenance mechanism.

[0011] As a preferred embodiment of the present invention, the monitoring and analysis process of the abnormal risk value by the monitoring and evaluation unit is as follows:

[0012] Step 1: Perform operation collection on the intelligent warehousing operation process, and mark the collection time as the time threshold. Set the number of operation time periods covered by the time threshold as A, where A is a natural number greater than 1, to obtain the abnormal risk value within the time threshold. The abnormal risk value is expressed as the number of storage internal temperature values corresponding to exceeding the preset temperature threshold. The storage internal temperature value is expressed as the number of storage internal temperature values corresponding to each sub-operation node in each operation time period that exceed the preset storage internal temperature value.

[0013] Step 2: Compare and analyze the abnormal risk value with the preset abnormal value. When the abnormal risk value is less than or equal to the preset abnormal risk value, no signal is generated, indicating that the cooling fan inside the warehouse is operating normally, and the warehouse is ventilated and cooled normally without any maintenance management. When the abnormal risk value is greater than the preset abnormal risk value ratio, an operation fault signal is generated.

[0014] As a preferred embodiment of the present invention, the internal fault screening unit performs the following evaluation and analysis process on the internal factor fault value:

[0015] Step 1: Obtain the internal fault factor values in each operating period, wherein the internal fault factor values include the operating power value of the cooling fan and the wind speed value of the air duct in the intelligent warehouse.

[0016] Step 2: Compare the cooling fan operating speed value and the duct wind speed value with the preset cooling fan operating speed value and the preset duct wind speed value respectively; when the cooling fan operating speed value is greater than or equal to the preset cooling fan operating speed value and the duct wind speed value is greater than or equal to the preset duct wind speed value, generate a component normal operation signal;

[0017] When the cooling fan operating speed value is less than the preset cooling fan operating speed value or the duct wind speed value is less than the preset duct wind speed value, a component operation fault signal is generated, and the component operation fault signal includes a cooling fan operation fault signal and an air duct blockage fault signal.

[0018] As a preferred embodiment of the present invention, when the control and analysis unit receives a component operation fault signal, the cooling fan operation state changes to perform an in-depth screening of the component operation fault signal, and the screening process is:

[0019] Step 1: The control feedback unit obtains the component operation fault signal, uses the cooling fan to extract the air in the smart storage into the air duct, and then exhausts it to the outside through the air duct until the wind speed sensor detects that the wind speed in the air duct reaches the set wind speed;

[0020] Step 2: Monitor the air duct. When the duct wind speed value does not reach the set duct wind speed value during the monitoring process, adjust the cooling fan operating rate value until it reaches the preset cooling fan operating rate value. If the duct wind speed value does not reach the set duct wind speed value, generate a duct confirmation operation fault signal. If the duct wind speed value reaches the preset duct wind speed value, generate a cooling fan confirmation operation fault signal. The cooling fan confirmation operation fault signal and the duct confirmation operation fault signal are deep screening confirmation fault signals, and the deep screening confirmation fault signal is sent to the control and analysis unit.

[0021] As a preferred embodiment of the present invention, the external interference elimination unit performs the following evaluation and analysis process for the external interference factor value:

[0022] Step 1: Obtaining external interference factor values during the monitoring operation period, wherein the external interference factor values include ambient temperature value, light intensity value, and ambient wind speed value, and the ambient temperature value, light intensity value, and ambient wind speed value are all average values during the monitoring process;

[0023] Step 2: Calculate the internal heat dissipation coefficient T of the warehouse based on the ambient temperature value, light intensity value and ambient wind speed value, T = (a1*W+a2*E) / a3*R, and a1, a2 and a3 are positive integers greater than 0, where a1, a2 and a3 are preset ratio factor coefficients of the ambient temperature value, light intensity value and ambient wind speed value respectively, W is the ambient temperature value, E is the light intensity value, and R is the ambient wind speed value. When the internal heat dissipation coefficient T of the warehouse is greater than or equal to the preset heat dissipation value, an intelligent warehouse confirmation high heat dissipation adjustment signal is generated; when the internal heat dissipation coefficient T of the warehouse is less than the preset heat dissipation value, an intelligent warehouse confirmation low heat dissipation adjustment signal is generated. The intelligent warehouse confirmation high heat dissipation adjustment signal and the intelligent warehouse low heat dissipation adjustment signal are operation adjustment signals, and the operation adjustment signal is sent to the control and analysis unit.

[0024] As a preferred embodiment of the present invention, the regulation analysis unit analyzes the regulation process as follows:

[0025] When a cooling fan operation fault confirmation signal or an air duct operation fault confirmation signal is obtained, the intelligent warehouse is judged to be affected by internal fault interference factors, a cleaning signal is generated, and the cleaning signal is sent to the environmental control center;

[0026] When the intelligent warehousing confirmation high heat dissipation adjustment signal and the intelligent warehousing confirmation low heat dissipation adjustment signal are received, a wind speed adjustment signal is generated and sent to the environment control center.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention mainly uses the internal fault screening unit to monitor the fluctuation of the intelligent warehouse ventilation wind speed to analyze the operational faults of the intelligent warehouse, and uses whether the duct wind speed value exceeds the preset threshold as the basis for judging whether the internal ventilation and heat dissipation of the intelligent warehouse has an operational fault. If the judgment generates a component operation fault signal, the operating parameters of the operation fault are adjusted and monitored to achieve accurate screening so as to quickly carry out the corresponding maintenance or cleaning links; if the component operation normal signal is generated, it is combined with the external interference elimination unit to assist in eliminating the interference of external factors, improve the accuracy of the internal fault factor judgment, and after eliminating the influence of the internal factor fault, the internal ventilation and heat dissipation effect of the intelligent warehouse is adjusted in real time according to the external interference factors, so as to achieve effective heat dissipation in high temperature weather and energy-saving effect of low temperature heat dissipation. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0030] Figure 1 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0031] The following is a clear and complete description of the technical solutions of the present invention in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0032] Example 1:

[0033] See also Figure 1 As shown, an intelligent warehouse management system based on data processing technology includes an environment control center, a data acquisition unit, a monitoring and evaluation unit, an internal fault screening unit, an external interference elimination unit, a control and analysis unit, and an alarm unit;

[0034] The environmental control center generates an operation fault judgment instruction and sends the operation fault judgment instruction to the data acquisition unit. The data acquisition unit is used to collect abnormal risk values and abnormal interference factor values inside the warehouse. The abnormal interference factor values include internal fault factor values and external interference factor values, and transmit the abnormal risk values, internal fault factor values and external interference factor values to the monitoring and evaluation unit, internal fault screening unit and external interference elimination unit respectively.

[0035] The monitoring and evaluation unit receives the abnormal risk value and performs monitoring and analysis on the abnormal risk value. The monitoring and analysis process is as follows:

[0036] Step 1: Collect data from the intelligent warehousing operation process and mark the collection duration as the duration threshold. Set the number of operation periods covered by the duration threshold as A, where A is a natural number greater than 1, to obtain the abnormal risk value within the duration threshold. The abnormal risk value is expressed as the number of internal warehouse temperature values that exceed the preset temperature threshold. The internal warehouse temperature value is expressed as the number of internal warehouse temperature values corresponding to each sub-operation node in each operation period that exceed the preset internal warehouse temperature value.

[0037] Step 2: Compare and analyze the abnormal risk value with the preset abnormal value. When the abnormal risk value is less than or equal to the preset abnormal risk value, no signal is generated, indicating that the cooling fan inside the warehouse is operating normally, and the warehouse is ventilated and cooled normally without any maintenance management. When the abnormal risk value is greater than the preset abnormal risk value ratio, an operation fault signal is generated.

[0038] Whether the wind speed value in the air duct exceeds the preset threshold is used as a judgment to determine whether there is an operational failure in the ventilation and heat dissipation inside the intelligent warehouse. After obtaining the operational failure signal, it is sent to the internal failure screening unit and the alarm unit, and the alarm unit displays the fault code.

[0039] The internal fault screening unit receives the operation fault signal and evaluates and analyzes the internal factor fault value. The evaluation and analysis process is as follows:

[0040] Step 1: Obtain the internal fault factor values in each operating period, which include the operating power value of the cooling fan and the wind speed value of the air duct in the intelligent warehouse.

[0041] Step 2: Compare the cooling fan operating speed value and the duct wind speed value with the preset cooling fan operating speed value and the preset duct wind speed value respectively; when the cooling fan operating speed value is greater than or equal to the preset cooling fan operating speed value and the duct wind speed value is greater than or equal to the preset duct wind speed value, generate a component normal operation signal;

[0042] When the cooling fan operating speed value is less than the preset cooling fan operating speed value or the duct wind speed value is less than the preset duct wind speed value, a component operation fault signal is generated, and the component operation fault signal includes a cooling fan operation fault signal and an air duct blockage fault signal;

[0043] When the intelligent warehouse confirms that a component operation failure has occurred, the failure is caused by incorrect operation of the cooling fan or air duct. At the same time as the component operation failure signal is generated, the cooling fan operation rate value and the air duct wind speed value are compared and analyzed, and the component operation failure signal is sent to the control and analysis unit.

[0044] When the control and analysis unit receives a component operation fault signal, it adjusts the operating parameters of the cooling fan in the intelligent warehouse, monitors its operating status in real time during the cooling fan operation parameter adjustment process, and conducts in-depth screening of component operation fault signals based on changes in the cooling fan operation status. The screening process is as follows:

[0045] Step 1: The control feedback unit obtains the component operation fault signal, uses the cooling fan to extract the air in the smart storage into the air duct, and then exhausts it to the outside through the air duct. During the exhaust process, the wind speed sensor detects that the wind speed in the air duct reaches the set wind speed;

[0046] Step 2: Monitor the air duct. When the duct wind speed value does not reach the set duct wind speed value during the monitoring process, adjust the cooling fan operating rate value until it reaches the preset cooling fan operating rate value. If the duct wind speed value does not reach the set duct wind speed value, a duct confirmation operation fault signal is generated. If the wind speed value in the duct is too low, there will be too much impurities and dust on the duct inlet filter and there will be wind blocking. If the duct wind speed value reaches the preset duct wind speed value, a cooling fan confirmation operation fault signal is generated. The cooling fan confirmation operation fault signal and the duct confirmation operation fault signal are deep screening confirmation fault signals, and the deep screening confirmation fault signal is sent to the control and analysis unit.

[0047] When a cooling fan operation fault confirmation signal or an air duct operation fault confirmation signal is obtained, the intelligent warehouse is judged to be affected by internal fault interference factors, a cleaning signal is generated, and the cleaning signal is sent to the environmental control center to match maintenance personnel for maintenance processing.

[0048] The external interference elimination unit receives the external interference factor value and performs evaluation and elimination analysis on the external interference factor value. The evaluation and elimination analysis process is as follows:

[0049] Step 1: Obtain the external interference factor values during the monitoring operation period. The external interference factor values include the ambient temperature value, the light intensity value, and the ambient wind speed value. The ambient temperature value, the light intensity value, and the ambient wind speed value are all average values during the monitoring process.

[0050] Step 2: Calculate the internal heat dissipation coefficient T of the warehouse based on the ambient temperature value, light intensity value and ambient wind speed value, T = (a1*W+a2*E) / a3*R, and a1, a2 and a3 are positive integers greater than 0, where a1, a2 and a3 are preset ratio factor coefficients of the ambient temperature value, light intensity value and ambient wind speed value respectively. The preset ratio factor coefficients are suitable for de-dimensionalization. W is the ambient temperature value, E is the light intensity value, and R is the ambient wind speed value. When the internal heat dissipation coefficient T of the warehouse is greater than the preset heat dissipation value, an intelligent warehouse confirmation high heat dissipation adjustment signal is generated. When the internal heat dissipation coefficient T of the warehouse is less than the preset heat dissipation value, an intelligent warehouse confirmation low heat dissipation adjustment signal is generated. The intelligent warehouse confirmation high heat dissipation adjustment signal and the intelligent warehouse low heat dissipation adjustment signal are operation adjustment signals, and the operation adjustment signal is sent to the control and analysis unit.

[0051] When the control and analysis unit receives the intelligent warehouse confirmation high heat dissipation adjustment signal and the intelligent warehouse confirmation low heat dissipation adjustment signal, it adjusts the operating parameters of the heat dissipation fan in the intelligent warehouse and adjusts the preset air duct wind speed value. During the adjustment process of the heat dissipation fan operating parameters, its operating status is simultaneously monitored in real time until the wind speed sensor detects that the wind speed in the air duct reaches the preset air duct wind speed value, and then generates a normal operation signal.

[0052] To summarize, the present invention firstly uses the internal fault screening unit as the main unit to monitor the fluctuation of the intelligent warehouse ventilation wind speed to analyze the operational faults of the intelligent warehouse, and uses whether the duct wind speed value exceeds the preset threshold as the basis for judging whether there is an operational fault in the intelligent warehouse internal ventilation and heat dissipation. If the judgment generates a component operation fault signal, the operating parameters of the operation fault are adjusted and monitored to achieve accurate screening so as to quickly carry out the corresponding maintenance or cleaning links; if the component operation normal signal is generated, it is combined with the external interference elimination unit to assist in eliminating the interference of external factors, improve the accuracy of the internal fault factor judgment, and after eliminating the influence of the internal factor fault, the internal ventilation and heat dissipation effect of the intelligent warehouse is adjusted in real time according to the external interference factors, so as to achieve effective heat dissipation in high temperature weather and energy-saving effect of low temperature heat dissipation.

[0053] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent warehouse management system based on data processing technology, characterized in that: It includes environmental control center, data acquisition unit, monitoring and evaluation unit, internal fault screening unit, external interference elimination unit, control and analysis unit and alarm unit; The environmental control center generates an operation fault determination instruction and sends the operation fault determination instruction to the data acquisition unit. The data acquisition unit is used to collect abnormal risk values and abnormal interference factor values inside the warehouse. The abnormal interference factor values include internal fault factor values and external interference factor values, and transmit the abnormal risk values, internal fault factor values and external interference factor values to the monitoring and evaluation unit, the internal fault screening unit, and the external interference elimination unit respectively; The monitoring and evaluation unit receives the abnormal risk value, monitors and analyzes the abnormal risk value, and sends the acquired operation fault signal to the internal fault screening unit and the alarm unit; The internal fault screening unit receives the operation fault signal, evaluates and analyzes the internal fault, and sends the obtained component operation fault signal to the control and analysis unit; The external interference elimination unit receives the external interference factor value, evaluates and eliminates the external interference factor value, and sends the obtained operation adjustment signal to the control analysis unit; The control and analysis unit receives component operation fault signals and operation adjustment signals, generates a cleaning signal or a wind speed adjustment signal, and sends the cleaning signal or the wind speed adjustment signal to the environmental control center to match the corresponding maintenance mechanism.

2. The intelligent warehouse management system based on data processing technology according to claim 1 is characterized in that: The monitoring and analysis process of the abnormal risk value by the monitoring and evaluation unit is as follows: Step 1: Perform operation collection on the intelligent warehousing operation process, and mark the collection time as the time threshold. Set the number of operation time periods covered by the time threshold as A, where A is a natural number greater than 1, to obtain the abnormal risk value within the time threshold. The abnormal risk value is expressed as the number of storage internal temperature values corresponding to exceeding the preset temperature threshold. The storage internal temperature value is expressed as the number of storage internal temperature values corresponding to each sub-operation node in each operation time period that exceed the preset storage internal temperature value. Step 2: Compare and analyze the abnormal risk value with the preset abnormal value. When the abnormal risk value is less than or equal to the preset abnormal risk value, no signal is generated, indicating that the cooling fan inside the warehouse is operating normally, and the warehouse is ventilated and cooled normally without any maintenance management. When the abnormal risk value is greater than the preset abnormal risk value ratio, an operation fault signal is generated.

3. The intelligent warehouse management system based on data processing technology according to claim 2 is characterized in that: The evaluation and analysis process of the internal factor fault value by the internal fault screening unit is as follows: Step 1: Obtain the internal fault factor values in each operating period, wherein the internal fault factor values include the operating power value of the cooling fan and the wind speed value of the air duct in the intelligent warehouse. Step 2: Compare the cooling fan operating speed value and the duct wind speed value with the preset cooling fan operating speed value and the preset duct wind speed value respectively; when the cooling fan operating speed value is greater than or equal to the preset cooling fan operating speed value and the duct wind speed value is greater than or equal to the preset duct wind speed value, generate a component normal operation signal; When the cooling fan operating speed value is less than the preset cooling fan operating speed value or the duct wind speed value is less than the preset duct wind speed value, a component operation fault signal is generated, and the component operation fault signal includes a cooling fan operation fault signal and an air duct blockage fault signal.

4. The intelligent warehouse management system based on data processing technology according to claim 3 is characterized in that: When the control and analysis unit receives a component operation fault signal, the cooling fan operation state changes to perform an in-depth screening of the component operation fault signal, and the screening process is: Step 1: The control feedback unit obtains the component operation fault signal, uses the cooling fan to extract the air in the smart storage into the air duct, and then exhausts it to the outside through the air duct until the wind speed sensor detects that the wind speed in the air duct reaches the set wind speed; Step 2: Monitor the air duct. When the duct wind speed value does not reach the set duct wind speed value during the monitoring process, adjust the cooling fan operating rate value until it reaches the preset cooling fan operating rate value. If the duct wind speed value does not reach the set duct wind speed value, generate a duct confirmation operation fault signal. If the duct wind speed value reaches the preset duct wind speed value, generate a cooling fan confirmation operation fault signal. The cooling fan confirmation operation fault signal and the duct confirmation operation fault signal are deep screening confirmation fault signals, and the deep screening confirmation fault signal is sent to the control and analysis unit.

5. The intelligent warehouse management system based on data processing technology according to claim 4 is characterized in that: The evaluation and analysis process of the external interference elimination unit for the external interference factor value is as follows: Step 1: Obtaining external interference factor values during the monitoring operation period, wherein the external interference factor values include ambient temperature value, light intensity value, and ambient wind speed value, and the ambient temperature value, light intensity value, and ambient wind speed value are all average values during the monitoring process; Step 2: Calculate the internal heat dissipation coefficient T of the warehouse based on the ambient temperature value, light intensity value and ambient wind speed value, T = (a1*W+a2*E) / a3*R, and a1, a2 and a3 are positive integers greater than 0, where a1, a2 and a3 are preset ratio factor coefficients of the ambient temperature value, light intensity value and ambient wind speed value respectively, W is the ambient temperature value, E is the light intensity value, and R is the ambient wind speed value. When the internal heat dissipation coefficient T of the warehouse is greater than or equal to the preset heat dissipation value, an intelligent warehouse confirmation high heat dissipation adjustment signal is generated; when the internal heat dissipation coefficient T of the warehouse is less than the preset heat dissipation value, an intelligent warehouse confirmation low heat dissipation adjustment signal is generated. The intelligent warehouse confirmation high heat dissipation adjustment signal and the intelligent warehouse low heat dissipation adjustment signal are operation adjustment signals, and the operation adjustment signal is sent to the control and analysis unit.

6. The intelligent warehouse management system based on data processing technology according to claim 5 is characterized in that: The regulation and control analysis unit analyzes the regulation and control process as follows: When a cooling fan operation fault confirmation signal or an air duct operation fault confirmation signal is obtained, the intelligent warehouse is judged to be affected by internal fault interference factors, a cleaning signal is generated, and the cleaning signal is sent to the environmental control center; When the intelligent warehousing confirmation high heat dissipation adjustment signal and the intelligent warehousing confirmation low heat dissipation adjustment signal are received, a wind speed adjustment signal is generated and sent to the environment control center.

Images