获取两个日期之间的总机器 运行 小时,但分为 3 个时间范围:标准时间、高峰时间和非高峰时间
Get the total machine running hours between two dates but split into 3 time ranges: standard time, peak time and off-peak time
获取两个日期之间的运行宁小时但分为3个时间运行ges:标准时间、高峰时间和非高峰时间。
上下文
编程环境: Wonderware ArchestrA
编程语言: ArchestrA Quick Script .Net
数据库:Historian - SQL 服务器(In-SQL)
外部: 采矿业中的一对泵,需要了解 3 个不同电价时间(高峰、标准、非高峰时间)期间泵的使用情况。
工作日:
标准时间: 09:00 至 17:00 AND 19:00 至 22:00
高峰时间: 06:00 至 09:00 AND 17:00 至 19:00
非高峰时间: 22:00 至 06:00
星期六:
标准时间: 07:00 至 12:00 AND 18:00 至 20:00
非高峰时间: 20:00 至 07:00 AND 12:00 至 18:00
周日:
淡季:整个星期天都是淡季
我需要
两个日期之间:
- 高峰时段的泵总小时数 运行。
- 非高峰时段泵总小时数 运行。
- 标准时间内的总泵送时间 运行。
我试过的方法:(机器 运行 的总非高峰时间,以小时为单位)。
它有效,但大多数时候我得到的时间少于我应该得到的时间。
-- This script only gets the total off-peak time hours
SET NOCOUNT ON
DECLARE @StartDate DateTime
DECLARE @EndDate DateTime
DECLARE @var1 REAL;
DECLARE @var2 REAL;
DECLARE @var3 REAL;
SET @StartDate = '2015/08/01 05:00:00.000'
SET @EndDate = GetDate()
SET NOCOUNT OFF
SET @var1 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (2, 3, 4, 5, 6, 7)
)
SET @var2 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '20:00:00' AND CAST(DateTime as time) < '07:00:00')
)
SET @var3 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '12:00:00' AND CAST(DateTime as time) < '18:00:00')
)
IF @var1 IS NULL SET @var1 = 0
IF @var2 IS NULL SET @var2 = 0
IF @var3 IS NULL SET @var3 = 0
SELECT
'Count' = (Count(DiscreteHistory.Value)/60.0) + @var1 + @var2 + @var3
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 7)
AND (CAST(DateTime as time) >= '22:00:00' OR CAST(DateTime as time) < '06:00:00');
谢谢。
示例数据
我将以下信息记录到数据库中:
运行 反馈的唯一标记名称:KDCE_S04_22PMP01_Machine.FA_RF 这是一个 运行 反馈,它是“1”或“0” " 或 "null" 值
机器运行宁小时的唯一标签名称:me.a0_MainPump.RunningHours.FA_PV这是泵量的整数值运行宁小时。
两个标签名称都与 TagName、Value、DateTime、quality 等一起记录。
我有一个 table,其中包括以下列:
| DateTime | TagName | Value | QualityDetail |
在数据库中获取示例数据的脚本:
SET NOCOUNT ON
DECLARE @StartDate DateTime
DECLARE @EndDate DateTime
SET @StartDate = '20150701 05:00:00.000'
SET @EndDate = '20150731 05:00:00.000'
SET NOCOUNT OFF
SELECT
DateTime, TagName, Value, Quality
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DateTime >= @StartDate AND DateTime <= @EndDate
如果我导出到 csv,它 returns 这个输出:(我已经缩短了它)
DateTime,TagName,Value,Quality
2015/07/01 05:00:00 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,133
2015/07/01 05:09:46 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 05:09:53 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 06:44:20 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 06:45:54 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 07:36:22 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 07:36:48 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 01:53:44 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 01:53:44 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 02:04:52 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 02:05:27 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 02:07:25 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 02:09:13 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 02:14:54 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 12:10:48 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/02 05:24:06 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 05:24:16 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/02 05:50:52 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 05:50:59 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/02 06:00:15 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 06:55:18 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 06:55:18 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 09:46:58 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 09:46:58 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 01:30:27 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 01:30:27 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 05:38:03 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 07:01:56 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/03 03:41:09 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/03 09:05:18 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/03 10:42:00 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/03 10:57:31 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/03 04:53:36 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/04 10:08:17 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/05 06:43:50 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/05 09:43:08 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/05 01:04:03 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/06 09:37:53 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/06 11:07:15 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/06 11:29:48 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/06 05:02:38 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/07 06:15:33 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/07 06:32:24 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/07 09:05:20 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/07 01:10:09 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/07 01:10:16 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/07 04:45:12 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/07 08:19:40 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/07 09:01:35 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
好的,上面编辑的脚本现在工作正常,基本上我在每个时间范围(高峰、标准和非高峰)看到了下面代码的三种变体。
唯一的问题是,如果 PLC 和 Historian/SQL 数据库之间存在网络通信问题,那么您将获得 "loose" 数据,并且最终会在数据库中获得大量 "null" 读数。这就是为什么时间没有加起来的原因。更好的方法是以 SCADA IO 标签为代价在 PLC 中实现此功能。
尽管如此,下面的脚本仍然有效。
-- this script only gets the total off-peak time hours
SET NOCOUNT ON
DECLARE @StartDate DateTime
DECLARE @EndDate DateTime
DECLARE @var1 REAL;
DECLARE @var2 REAL;
DECLARE @var3 REAL;
SET @StartDate = '2015/08/01 05:00:00.000'
SET @EndDate = GetDate()
SET NOCOUNT OFF
SET @var1 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (2, 3, 4, 5, 6, 7)
)
SET @var2 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '20:00:00' AND CAST(DateTime as time) < '07:00:00')
)
SET @var3 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '12:00:00' AND CAST(DateTime as time) < '18:00:00')
)
IF @var1 IS NULL SET @var1 = 0
IF @var2 IS NULL SET @var2 = 0
IF @var3 IS NULL SET @var3 = 0
SELECT
'Count' = (Count(DiscreteHistory.Value)/60.0) + @var1 + @var2 + @var3
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 7)
AND (CAST(DateTime as time) >= '22:00:00' OR CAST(DateTime as time) < '06:00:00');
我不知道您是否仍需要有关此主题的帮助,但我们实际上使用事件系统在我们的泵不运行时触发 运行 并将记录插入我们自己的表中。该表有一个触发器,可以将 0 和 1 扁平化为单个记录,从而更容易分析数据。我们数据库的示例记录如下所示:
brake_start_time | brake_end_time | (downtime calculation) | (uptime before it broke) | reasons why it stopped working | comments
使用类似的概念,你可以简单地得到类似
的东西
pump_start_time | pump_end_time | runtime | run_category ( standard time, peak time and off-peak time )
获取两个日期之间的运行宁小时但分为3个时间运行ges:标准时间、高峰时间和非高峰时间。
上下文
编程环境: Wonderware ArchestrA
编程语言: ArchestrA Quick Script .Net
数据库:Historian - SQL 服务器(In-SQL)
外部: 采矿业中的一对泵,需要了解 3 个不同电价时间(高峰、标准、非高峰时间)期间泵的使用情况。
工作日:
标准时间: 09:00 至 17:00 AND 19:00 至 22:00
高峰时间: 06:00 至 09:00 AND 17:00 至 19:00
非高峰时间: 22:00 至 06:00
星期六:
标准时间: 07:00 至 12:00 AND 18:00 至 20:00
非高峰时间: 20:00 至 07:00 AND 12:00 至 18:00
周日:
淡季:整个星期天都是淡季
我需要
两个日期之间:
- 高峰时段的泵总小时数 运行。
- 非高峰时段泵总小时数 运行。
- 标准时间内的总泵送时间 运行。
我试过的方法:(机器 运行 的总非高峰时间,以小时为单位)。
它有效,但大多数时候我得到的时间少于我应该得到的时间。
-- This script only gets the total off-peak time hours
SET NOCOUNT ON
DECLARE @StartDate DateTime
DECLARE @EndDate DateTime
DECLARE @var1 REAL;
DECLARE @var2 REAL;
DECLARE @var3 REAL;
SET @StartDate = '2015/08/01 05:00:00.000'
SET @EndDate = GetDate()
SET NOCOUNT OFF
SET @var1 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (2, 3, 4, 5, 6, 7)
)
SET @var2 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '20:00:00' AND CAST(DateTime as time) < '07:00:00')
)
SET @var3 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '12:00:00' AND CAST(DateTime as time) < '18:00:00')
)
IF @var1 IS NULL SET @var1 = 0
IF @var2 IS NULL SET @var2 = 0
IF @var3 IS NULL SET @var3 = 0
SELECT
'Count' = (Count(DiscreteHistory.Value)/60.0) + @var1 + @var2 + @var3
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 7)
AND (CAST(DateTime as time) >= '22:00:00' OR CAST(DateTime as time) < '06:00:00');
谢谢。
示例数据
我将以下信息记录到数据库中:
运行 反馈的唯一标记名称:KDCE_S04_22PMP01_Machine.FA_RF 这是一个 运行 反馈,它是“1”或“0” " 或 "null" 值
机器运行宁小时的唯一标签名称:me.a0_MainPump.RunningHours.FA_PV这是泵量的整数值运行宁小时。
两个标签名称都与 TagName、Value、DateTime、quality 等一起记录。
我有一个 table,其中包括以下列:
| DateTime | TagName | Value | QualityDetail |
在数据库中获取示例数据的脚本:
SET NOCOUNT ON
DECLARE @StartDate DateTime
DECLARE @EndDate DateTime
SET @StartDate = '20150701 05:00:00.000'
SET @EndDate = '20150731 05:00:00.000'
SET NOCOUNT OFF
SELECT
DateTime, TagName, Value, Quality
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DateTime >= @StartDate AND DateTime <= @EndDate
如果我导出到 csv,它 returns 这个输出:(我已经缩短了它)
DateTime,TagName,Value,Quality
2015/07/01 05:00:00 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,133
2015/07/01 05:09:46 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 05:09:53 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 06:44:20 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 06:45:54 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 07:36:22 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 07:36:48 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 01:53:44 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 01:53:44 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 02:04:52 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 02:05:27 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 02:07:25 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/01 02:09:13 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/01 02:14:54 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 12:10:48 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/02 05:24:06 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 05:24:16 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/02 05:50:52 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 05:50:59 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/02 06:00:15 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 06:55:18 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 06:55:18 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 09:46:58 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 09:46:58 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 01:30:27 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/02 01:30:27 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 05:38:03 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/02 07:01:56 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/03 03:41:09 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/03 09:05:18 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/03 10:42:00 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/03 10:57:31 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/03 04:53:36 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/04 10:08:17 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/05 06:43:50 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/05 09:43:08 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/05 01:04:03 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/06 09:37:53 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/06 11:07:15 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/06 11:29:48 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/06 05:02:38 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/07 06:15:33 AM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/07 06:32:24 AM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/07 09:05:20 AM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/07 01:10:09 PM,KDCE_S04_22PMP01_Machine.FA_RF,(null),1
2015/07/07 01:10:16 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/07 04:45:12 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
2015/07/07 08:19:40 PM,KDCE_S04_22PMP01_Machine.FA_RF,1,0
2015/07/07 09:01:35 PM,KDCE_S04_22PMP01_Machine.FA_RF,0,0
好的,上面编辑的脚本现在工作正常,基本上我在每个时间范围(高峰、标准和非高峰)看到了下面代码的三种变体。
唯一的问题是,如果 PLC 和 Historian/SQL 数据库之间存在网络通信问题,那么您将获得 "loose" 数据,并且最终会在数据库中获得大量 "null" 读数。这就是为什么时间没有加起来的原因。更好的方法是以 SCADA IO 标签为代价在 PLC 中实现此功能。
尽管如此,下面的脚本仍然有效。
-- this script only gets the total off-peak time hours
SET NOCOUNT ON
DECLARE @StartDate DateTime
DECLARE @EndDate DateTime
DECLARE @var1 REAL;
DECLARE @var2 REAL;
DECLARE @var3 REAL;
SET @StartDate = '2015/08/01 05:00:00.000'
SET @EndDate = GetDate()
SET NOCOUNT OFF
SET @var1 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (2, 3, 4, 5, 6, 7)
)
SET @var2 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '20:00:00' AND CAST(DateTime as time) < '07:00:00')
)
SET @var3 =
(
SELECT
'Count' = Count(DiscreteHistory.Value)/60.0
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 2, 3, 4, 5, 6)
AND (CAST(DateTime as time) >= '12:00:00' AND CAST(DateTime as time) < '18:00:00')
)
IF @var1 IS NULL SET @var1 = 0
IF @var2 IS NULL SET @var2 = 0
IF @var3 IS NULL SET @var3 = 0
SELECT
'Count' = (Count(DiscreteHistory.Value)/60.0) + @var1 + @var2 + @var3
FROM
DiscreteHistory
WHERE
DiscreteHistory.TagName
IN ('KDCE_S04_22PMP01_Machine.FA_RF')
AND DiscreteHistory.Value = 1
AND wwRetrievalMode = 'Cyclic'
AND wwResolution = 60000
AND DateTime >= @StartDate
AND DateTime <= @EndDate
AND DATEPART(dw, DateTime) NOT IN (1, 7)
AND (CAST(DateTime as time) >= '22:00:00' OR CAST(DateTime as time) < '06:00:00');
我不知道您是否仍需要有关此主题的帮助,但我们实际上使用事件系统在我们的泵不运行时触发 运行 并将记录插入我们自己的表中。该表有一个触发器,可以将 0 和 1 扁平化为单个记录,从而更容易分析数据。我们数据库的示例记录如下所示:
brake_start_time | brake_end_time | (downtime calculation) | (uptime before it broke) | reasons why it stopped working | comments
使用类似的概念,你可以简单地得到类似
的东西pump_start_time | pump_end_time | runtime | run_category ( standard time, peak time and off-peak time )